Overview

Brought to you by YData

Dataset statistics

 Raw Dataset ProfilePreprocessed Dataset Profile
Number of variables5316
Number of observations7042319359
Missing cells84204513470
Missing cells (%)22.6%4.3%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory147.8 MiB26.7 MiB
Average record size in memory2.1 KiB1.4 KiB

Variable types

 Raw Dataset ProfilePreprocessed Dataset Profile
Numeric152
Text3014
DateTime40
Unsupported40

Alerts

Raw Dataset ProfilePreprocessed Dataset Profile
ref has constant value "GARANTIA-ES" Alert not present in this datasetConstant
company_id is highly overall correlated with dire_recogida_id and 3 other fieldsAlert not present in this datasetHigh correlation
dire_envio_id is highly overall correlated with dire_recogida_idAlert not present in this datasetHigh correlation
dire_recogida_id is highly overall correlated with company_id and 3 other fieldsAlert not present in this datasetHigh correlation
estado is highly overall correlated with id_estadoAlert not present in this datasetHigh correlation
estadofr is highly overall correlated with id_tipo and 1 other fieldsAlert not present in this datasetHigh correlation
id is highly overall correlated with id_piezaAlert not present in this datasetHigh correlation
id_estado is highly overall correlated with estadoAlert not present in this datasetHigh correlation
id_pieza is highly overall correlated with idAlert not present in this datasetHigh correlation
id_tipo is highly overall correlated with estadofr and 1 other fieldsAlert not present in this datasetHigh correlation
tipo is highly overall correlated with estadofr and 1 other fieldsAlert not present in this datasetHigh correlation
user_id is highly overall correlated with company_id and 2 other fieldsAlert not present in this datasetHigh correlation
user_id_pieza is highly overall correlated with company_id and 2 other fieldsAlert not present in this datasetHigh correlation
volumen3 is highly overall correlated with company_idAlert not present in this datasetHigh correlation
modification_date has 8751 (12.4%) missing values Alert not present in this datasetMissing
pedido_sage has 70423 (100.0%) missing values Alert not present in this datasetMissing
abono_sage has 70423 (100.0%) missing values Alert not present in this datasetMissing
pedido_a3 has 9730 (13.8%) missing values Alert not present in this datasetMissing
abono_a3 has 23679 (33.6%) missing values Alert not present in this datasetMissing
personaaz has 32790 (46.6%) missing values Alert not present in this datasetMissing
dire_envio_id has 27434 (39.0%) missing values Alert not present in this datasetMissing
dire_recogida_id has 26779 (38.0%) missing values Alert not present in this datasetMissing
peso3 has 28236 (40.1%) missing values Alert not present in this datasetMissing
volumen3 has 70418 (> 99.9%) missing values Alert not present in this datasetMissing
c_mail has 67591 (96.0%) missing values Alert not present in this datasetMissing
c_tel has 67202 (95.4%) missing values Alert not present in this datasetMissing
c_obs has 68233 (96.9%) missing values Alert not present in this datasetMissing
accepted_client has 62173 (88.3%) missing values Alert not present in this datasetMissing
desc_problema has 4741 (6.7%) missing values Alert not present in this datasetMissing
codigo_incidencia has 1426 (2.0%) missing values Alert not present in this datasetMissing
id_pieza has 1426 (2.0%) missing values Alert not present in this datasetMissing
user_id_pieza has 1426 (2.0%) missing values Alert not present in this datasetMissing
cod_articulo has 1435 (2.0%) missing values Alert not present in this datasetMissing
descripcion has 19536 (27.7%) missing values Alert not present in this datasetMissing
num_serie has 1508 (2.1%) missing values Alert not present in this datasetMissing
factura_albaran has 30101 (42.7%) missing values Alert not present in this datasetMissing
problema has 1427 (2.0%) missing values Alert not present in this datasetMissing
is_replacement has 1426 (2.0%) missing values Alert not present in this datasetMissing
creation_date_pieza has 1426 (2.0%) missing values Alert not present in this datasetMissing
modification_date_pieza has 1426 (2.0%) missing values Alert not present in this datasetMissing
titulo_pt has 70423 (100.0%) missing values Alert not present in this datasetMissing
titulo_pt_tipo has 70423 (100.0%) missing values Alert not present in this datasetMissing
peso3 is highly skewed (γ1 = 205.1225851) Alert not present in this datasetSkewed
id_pieza is uniformly distributed Alert not present in this datasetUniform
pedido_sage is an unsupported type, check if it needs cleaning or further analysis Alert not present in this datasetUnsupported
abono_sage is an unsupported type, check if it needs cleaning or further analysis Alert not present in this datasetUnsupported
titulo_pt is an unsupported type, check if it needs cleaning or further analysis Alert not present in this datasetUnsupported
titulo_pt_tipo is an unsupported type, check if it needs cleaning or further analysis Alert not present in this datasetUnsupported
estadofr has 8624 (12.2%) zeros Alert not present in this datasetZeros
Alert not present in this datasetdesc_problema_translated has 543 (2.8%) missing values Missing
Alert not present in this datasetdescripcion_translated has 3752 (19.4%) missing values Missing
Alert not present in this datasetCAR4 has 9174 (47.4%) missing values Missing
Alert not present in this datasetid_pieza has unique values Unique

Reproduction

 Raw Dataset ProfilePreprocessed Dataset Profile
Analysis started2024-12-29 10:08:27.2027052024-12-29 10:09:49.965068
Analysis finished2024-12-29 10:09:16.9386522024-12-29 10:09:53.562379
Duration49.74 seconds3.6 seconds
Software versionydata-profiling vv4.12.1ydata-profiling vv4.12.1
Download configurationconfig.jsonconfig.json

Variables

id
Real number (ℝ)

Distinct45183
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42013.347
Minimum19552
Maximum64750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:05.671129image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum19552
5-th percentile21855.1
Q130759.5
median42030
Q353026
95-th percentile62304.9
Maximum64750
Range45198
Interquartile range (IQR)22266.5

Descriptive statistics

Standard deviation12919.063
Coefficient of variation (CV)0.30749901
Kurtosis-1.1881978
Mean42013.347
Median Absolute Deviation (MAD)11130
Skewness0.0016870059
Sum2.9587059 × 109
Variance1.6690218 × 108
MonotonicityNot monotonic
2024-12-29T11:10:05.848722image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40833 146
 
0.2%
42953 95
 
0.1%
58596 64
 
0.1%
25643 60
 
0.1%
54003 59
 
0.1%
27115 57
 
0.1%
47498 57
 
0.1%
42244 56
 
0.1%
21319 56
 
0.1%
46170 50
 
0.1%
Other values (45173) 69723
99.0%
ValueCountFrequency (%)
19552 2
 
< 0.1%
19553 1
 
< 0.1%
19554 10
< 0.1%
19555 1
 
< 0.1%
19556 1
 
< 0.1%
19557 3
 
< 0.1%
19558 1
 
< 0.1%
19559 1
 
< 0.1%
19560 1
 
< 0.1%
19561 1
 
< 0.1%
ValueCountFrequency (%)
64750 1
 
< 0.1%
64749 6
< 0.1%
64748 1
 
< 0.1%
64747 1
 
< 0.1%
64746 1
 
< 0.1%
64745 1
 
< 0.1%
64744 1
 
< 0.1%
64743 1
 
< 0.1%
64742 1
 
< 0.1%
64741 1
 
< 0.1%

web_id
Real number (ℝ)

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.637803
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:05.986455image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile3
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.70092909
Coefficient of variation (CV)0.42796911
Kurtosis0.31401878
Mean1.637803
Median Absolute Deviation (MAD)1
Skewness0.8086284
Sum115339
Variance0.49130159
MonotonicityNot monotonic
2024-12-29T11:10:06.123103image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
1 34150
48.5%
2 27978
39.7%
3 8121
 
11.5%
5 174
 
0.2%
ValueCountFrequency (%)
1 34150
48.5%
2 27978
39.7%
3 8121
 
11.5%
5 174
 
0.2%
ValueCountFrequency (%)
5 174
 
0.2%
3 8121
 
11.5%
2 27978
39.7%
1 34150
48.5%

codigo
['Text', 'Text']

 Raw Dataset ProfilePreprocessed Dataset Profile
Distinct4518315226
Distinct (%)64.2%78.7%
Missing00
Missing (%)0.0%0.0%
Memory size4.5 MiB1.2 MiB
2024-12-29T11:10:06.581364image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

 Raw Dataset ProfilePreprocessed Dataset Profile
Max length1010
Median length1010
Mean length1010
Min length1010

Characters and Unicode

 Raw Dataset ProfilePreprocessed Dataset Profile
Total characters704230193590
Distinct characters3636
Distinct categories22 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Raw Dataset ProfilePreprocessed Dataset Profile
Unique3672513191 ?
Unique (%)52.1%68.1%

Sample

 Raw Dataset ProfilePreprocessed Dataset Profile
1st rowMGHQM2LT55MMZPL2LO50
2nd rowMGHQM2LT55MMZPL2LO50
3rd rowLMPOM2TR8BMMZPL2LO50
4th rowLMNWLG1U1AL2VQL2LVF3
5th rowLMNWLG1U1ALGRPLMLUAE
ValueCountFrequency (%)
bgvjymat77 146
 
0.2%
m5iwmzznd9 95
 
0.1%
m2dqbgdm0b 64
 
0.1%
am9pa21s32 60
 
0.1%
ljqcmz1m00 59
 
0.1%
b29ozmzv3e 57
 
0.1%
m5ebm5dj2f 57
 
0.1%
y2plz2ky3a 56
 
0.1%
k2lrmg5r5b 56
 
0.1%
njgel5plb9 50
 
0.1%
Other values (45173) 69723
99.0%
ValueCountFrequency (%)
ljgbmptkdd 30
 
0.2%
ljgwljdh31 27
 
0.1%
agxlzwoxb3 25
 
0.1%
bgtta2lw64 24
 
0.1%
zmtlz2sy49 24
 
0.1%
ag1jyggzba 23
 
0.1%
zmdpzwmcb8 22
 
0.1%
zwliymcc1b 22
 
0.1%
awdpywcv33 21
 
0.1%
zmpoa2zvdc 20
 
0.1%
Other values (15216) 19121
98.8%
2024-12-29T11:10:07.177801image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 62637
 
8.9%
Z 47777
 
6.8%
A 41249
 
5.9%
L 40895
 
5.8%
2 35577
 
5.1%
W 35262
 
5.0%
G 32352
 
4.6%
P 29018
 
4.1%
N 27928
 
4.0%
B 26003
 
3.7%
Other values (26) 325532
46.2%
ValueCountFrequency (%)
M 16536
 
8.5%
Z 13193
 
6.8%
A 11705
 
6.0%
L 11297
 
5.8%
W 9959
 
5.1%
2 9278
 
4.8%
G 9016
 
4.7%
B 8130
 
4.2%
P 7863
 
4.1%
5 6315
 
3.3%
Other values (26) 90298
46.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 567916
80.6%
Decimal Number 136314
 
19.4%
ValueCountFrequency (%)
Uppercase Letter 155220
80.2%
Decimal Number 38370
 
19.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 62637
 
11.0%
Z 47777
 
8.4%
A 41249
 
7.3%
L 40895
 
7.2%
W 35262
 
6.2%
G 32352
 
5.7%
P 29018
 
5.1%
N 27928
 
4.9%
B 26003
 
4.6%
D 21524
 
3.8%
Other values (16) 203271
35.8%
ValueCountFrequency (%)
M 16536
 
10.7%
Z 13193
 
8.5%
A 11705
 
7.5%
L 11297
 
7.3%
W 9959
 
6.4%
G 9016
 
5.8%
B 8130
 
5.2%
P 7863
 
5.1%
N 6016
 
3.9%
D 5933
 
3.8%
Other values (16) 55572
35.8%
Decimal Number
ValueCountFrequency (%)
2 35577
26.1%
5 21034
15.4%
1 15557
11.4%
9 10751
 
7.9%
3 9209
 
6.8%
0 9038
 
6.6%
4 8937
 
6.6%
7 8795
 
6.5%
8 8772
 
6.4%
6 8644
 
6.3%
ValueCountFrequency (%)
2 9278
24.2%
5 6315
16.5%
1 4776
12.4%
9 3162
 
8.2%
3 2640
 
6.9%
4 2507
 
6.5%
7 2475
 
6.5%
8 2439
 
6.4%
0 2398
 
6.2%
6 2380
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 567916
80.6%
Common 136314
 
19.4%
ValueCountFrequency (%)
Latin 155220
80.2%
Common 38370
 
19.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 62637
 
11.0%
Z 47777
 
8.4%
A 41249
 
7.3%
L 40895
 
7.2%
W 35262
 
6.2%
G 32352
 
5.7%
P 29018
 
5.1%
N 27928
 
4.9%
B 26003
 
4.6%
D 21524
 
3.8%
Other values (16) 203271
35.8%
ValueCountFrequency (%)
M 16536
 
10.7%
Z 13193
 
8.5%
A 11705
 
7.5%
L 11297
 
7.3%
W 9959
 
6.4%
G 9016
 
5.8%
B 8130
 
5.2%
P 7863
 
5.1%
N 6016
 
3.9%
D 5933
 
3.8%
Other values (16) 55572
35.8%
Common
ValueCountFrequency (%)
2 35577
26.1%
5 21034
15.4%
1 15557
11.4%
9 10751
 
7.9%
3 9209
 
6.8%
0 9038
 
6.6%
4 8937
 
6.6%
7 8795
 
6.5%
8 8772
 
6.4%
6 8644
 
6.3%
ValueCountFrequency (%)
2 9278
24.2%
5 6315
16.5%
1 4776
12.4%
9 3162
 
8.2%
3 2640
 
6.9%
4 2507
 
6.5%
7 2475
 
6.5%
8 2439
 
6.4%
0 2398
 
6.2%
6 2380
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 704230
100.0%
ValueCountFrequency (%)
ASCII 193590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 62637
 
8.9%
Z 47777
 
6.8%
A 41249
 
5.9%
L 40895
 
5.8%
2 35577
 
5.1%
W 35262
 
5.0%
G 32352
 
4.6%
P 29018
 
4.1%
N 27928
 
4.0%
B 26003
 
3.7%
Other values (26) 325532
46.2%
ValueCountFrequency (%)
M 16536
 
8.5%
Z 13193
 
6.8%
A 11705
 
6.0%
L 11297
 
5.8%
W 9959
 
5.1%
2 9278
 
4.8%
G 9016
 
4.7%
B 8130
 
4.2%
P 7863
 
4.1%
5 6315
 
3.3%
Other values (26) 90298
46.6%
Distinct45070
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size550.3 KiB
Minimum2020-01-02 09:04:37
Maximum2024-09-30 18:10:26
Invalid dates0
Invalid dates (%)0.0%
2024-12-29T11:10:07.344836image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2024-12-29T11:10:07.512114image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct37979
Distinct (%)61.6%
Missing8751
Missing (%)12.4%
Memory size550.3 KiB
Minimum2020-01-03 07:32:48
Maximum2024-11-19 16:30:41
Invalid dates0
Invalid dates (%)0.0%
2024-12-29T11:10:07.705580image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2024-12-29T11:10:07.913732image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

company_id
Real number (ℝ)

Distinct3422
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1862.1276
Minimum0
Maximum8182
Zeros354
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:08.123428image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile61
Q1293
median743
Q33177
95-th percentile6120.8
Maximum8182
Range8182
Interquartile range (IQR)2884

Descriptive statistics

Standard deviation2065.8092
Coefficient of variation (CV)1.1093811
Kurtosis0.10812841
Mean1862.1276
Median Absolute Deviation (MAD)676
Skewness1.1124229
Sum1.3113661 × 108
Variance4267567.6
MonotonicityNot monotonic
2024-12-29T11:10:08.305947image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301 3940
 
5.6%
67 1662
 
2.4%
61 1372
 
1.9%
496 988
 
1.4%
7 968
 
1.4%
199 895
 
1.3%
654 815
 
1.2%
363 766
 
1.1%
494 753
 
1.1%
234 718
 
1.0%
Other values (3412) 57546
81.7%
ValueCountFrequency (%)
0 354
 
0.5%
7 968
1.4%
14 17
 
< 0.1%
15 93
 
0.1%
16 492
0.7%
21 5
 
< 0.1%
28 1
 
< 0.1%
29 12
 
< 0.1%
30 2
 
< 0.1%
31 268
 
0.4%
ValueCountFrequency (%)
8182 1
 
< 0.1%
8181 1
 
< 0.1%
8179 2
< 0.1%
8174 1
 
< 0.1%
8173 1
 
< 0.1%
8166 3
< 0.1%
8165 1
 
< 0.1%
8164 1
 
< 0.1%
8163 1
 
< 0.1%
8158 1
 
< 0.1%

user_id
Real number (ℝ)

Distinct4172
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3612.2618
Minimum2
Maximum10939
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:08.479422image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile118
Q1670
median3308
Q35894
95-th percentile8852
Maximum10939
Range10937
Interquartile range (IQR)5224

Descriptive statistics

Standard deviation2903.7748
Coefficient of variation (CV)0.80386611
Kurtosis-0.86498309
Mean3612.2618
Median Absolute Deviation (MAD)2602
Skewness0.48607415
Sum2.5438631 × 108
Variance8431908.4
MonotonicityNot monotonic
2024-12-29T11:10:08.654814image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3656 2709
 
3.8%
110 1372
 
1.9%
136 988
 
1.4%
1531 895
 
1.3%
4168 870
 
1.2%
504 766
 
1.1%
145 753
 
1.1%
471 699
 
1.0%
7604 675
 
1.0%
4396 650
 
0.9%
Other values (4162) 60046
85.3%
ValueCountFrequency (%)
2 5
 
< 0.1%
3 4
 
< 0.1%
25 72
 
0.1%
29 7
 
< 0.1%
59 5
 
< 0.1%
69 13
 
< 0.1%
70 1
 
< 0.1%
71 11
 
< 0.1%
72 2
 
< 0.1%
73 268
0.4%
ValueCountFrequency (%)
10939 1
 
< 0.1%
10938 1
 
< 0.1%
10936 2
< 0.1%
10931 1
 
< 0.1%
10930 1
 
< 0.1%
10923 3
< 0.1%
10922 1
 
< 0.1%
10921 1
 
< 0.1%
10920 1
 
< 0.1%
10915 1
 
< 0.1%
Distinct37717
Distinct (%)53.6%
Missing13
Missing (%)< 0.1%
Memory size5.3 MiB
2024-12-29T11:10:08.959425image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length75
Median length68
Mean length16.746087
Min length1

Characters and Unicode

Total characters1179092
Distinct characters131
Distinct categories16 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27232 ?
Unique (%)38.7%

Sample

1st rowPAL190646
2nd rowPAL190646
3rd rowCAMBIO TERMOSTATO LITE
4th rowPASARELAS SAMSUNG
5th rowPASARELAS SAMSUNG
ValueCountFrequency (%)
9774
 
6.3%
sav 2549
 
1.7%
renove 2052
 
1.3%
cf 1441
 
0.9%
cc 1303
 
0.8%
plan 1288
 
0.8%
reso 1068
 
0.7%
de 849
 
0.6%
clim 654
 
0.4%
pedido 653
 
0.4%
Other values (45834) 132397
86.0%
2024-12-29T11:10:09.789101image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96652
 
8.2%
2 85369
 
7.2%
85107
 
7.2%
1 62527
 
5.3%
A 51034
 
4.3%
E 49959
 
4.2%
3 48800
 
4.1%
4 39228
 
3.3%
C 38512
 
3.3%
S 34730
 
2.9%
Other values (121) 587174
49.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 472873
40.1%
Uppercase Letter 461673
39.2%
Lowercase Letter 105247
 
8.9%
Space Separator 85111
 
7.2%
Dash Punctuation 26635
 
2.3%
Other Punctuation 16892
 
1.4%
Other Symbol 3710
 
0.3%
Connector Punctuation 2941
 
0.2%
Open Punctuation 1305
 
0.1%
Close Punctuation 1265
 
0.1%
Other values (6) 1440
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13236
12.6%
a 11839
11.2%
o 8413
 
8.0%
i 8143
 
7.7%
r 8116
 
7.7%
n 6858
 
6.5%
l 6697
 
6.4%
s 5694
 
5.4%
t 5541
 
5.3%
c 5165
 
4.9%
Other values (35) 25545
24.3%
Uppercase Letter
ValueCountFrequency (%)
A 51034
11.1%
E 49959
10.8%
C 38512
 
8.3%
S 34730
 
7.5%
R 33994
 
7.4%
I 32768
 
7.1%
N 28715
 
6.2%
O 27863
 
6.0%
L 22479
 
4.9%
T 21780
 
4.7%
Other values (30) 119839
26.0%
Other Punctuation
ValueCountFrequency (%)
/ 9791
58.0%
. 3763
 
22.3%
, 1758
 
10.4%
* 454
 
2.7%
: 439
 
2.6%
' 212
 
1.3%
\ 127
 
0.8%
& 90
 
0.5%
; 82
 
0.5%
# 51
 
0.3%
Other values (6) 125
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 96652
20.4%
2 85369
18.1%
1 62527
13.2%
3 48800
10.3%
4 39228
8.3%
6 31780
 
6.7%
5 29132
 
6.2%
7 27765
 
5.9%
8 26034
 
5.5%
9 25586
 
5.4%
Math Symbol
ValueCountFrequency (%)
+ 546
98.0%
| 6
 
1.1%
< 3
 
0.5%
= 2
 
0.4%
Space Separator
ValueCountFrequency (%)
85107
> 99.9%
  4
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 1301
99.7%
[ 4
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1261
99.7%
] 4
 
0.3%
Other Letter
ValueCountFrequency (%)
º 760
88.3%
ª 101
 
11.7%
Modifier Symbol
ValueCountFrequency (%)
´ 2
66.7%
` 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 26635
100.0%
Other Symbol
ValueCountFrequency (%)
° 3710
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2941
100.0%
Control
ValueCountFrequency (%)
14
100.0%
Format
ValueCountFrequency (%)
­ 3
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 611312
51.8%
Latin 567780
48.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 51034
 
9.0%
E 49959
 
8.8%
C 38512
 
6.8%
S 34730
 
6.1%
R 33994
 
6.0%
I 32768
 
5.8%
N 28715
 
5.1%
O 27863
 
4.9%
L 22479
 
4.0%
T 21780
 
3.8%
Other values (76) 225946
39.8%
Common
ValueCountFrequency (%)
0 96652
15.8%
2 85369
14.0%
85107
13.9%
1 62527
10.2%
3 48800
8.0%
4 39228
6.4%
6 31780
 
5.2%
5 29132
 
4.8%
7 27765
 
4.5%
- 26635
 
4.4%
Other values (35) 78317
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1173190
99.5%
None 5902
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96652
 
8.2%
2 85369
 
7.3%
85107
 
7.3%
1 62527
 
5.3%
A 51034
 
4.4%
E 49959
 
4.3%
3 48800
 
4.2%
4 39228
 
3.3%
C 38512
 
3.3%
S 34730
 
3.0%
Other values (80) 581272
49.5%
None
ValueCountFrequency (%)
° 3710
62.9%
º 760
 
12.9%
é 233
 
3.9%
Ó 200
 
3.4%
ó 165
 
2.8%
Ñ 156
 
2.6%
Í 102
 
1.7%
ª 101
 
1.7%
ñ 78
 
1.3%
Á 67
 
1.1%
Other values (31) 330
 
5.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
2024-12-29T11:10:09.879761image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters70423
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
1 66304
94.2%
0 4119
 
5.8%
2024-12-29T11:10:10.080956image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 66304
94.2%
0 4119
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70423
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 66304
94.2%
0 4119
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 70423
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 66304
94.2%
0 4119
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 66304
94.2%
0 4119
 
5.8%
Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
2024-12-29T11:10:10.168503image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.0071852
Min length1

Characters and Unicode

Total characters70929
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 69918
99.3%
20 387
 
0.5%
30 45
 
0.1%
15 29
 
< 0.1%
10 21
 
< 0.1%
40 9
 
< 0.1%
25 4
 
< 0.1%
60 3
 
< 0.1%
50 3
 
< 0.1%
70 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
2024-12-29T11:10:10.417919image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70391
99.2%
2 391
 
0.6%
1 50
 
0.1%
3 45
 
0.1%
5 37
 
0.1%
4 9
 
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70929
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70391
99.2%
2 391
 
0.6%
1 50
 
0.1%
3 45
 
0.1%
5 37
 
0.1%
4 9
 
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 70929
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70391
99.2%
2 391
 
0.6%
1 50
 
0.1%
3 45
 
0.1%
5 37
 
0.1%
4 9
 
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70929
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70391
99.2%
2 391
 
0.6%
1 50
 
0.1%
3 45
 
0.1%
5 37
 
0.1%
4 9
 
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%

pedido_sage
Unsupported

Missing70423
Missing (%)100.0%
Memory size550.3 KiB

abono_sage
Unsupported

Missing70423
Missing (%)100.0%
Memory size550.3 KiB
Distinct38409
Distinct (%)63.3%
Missing9730
Missing (%)13.8%
Memory size4.3 MiB
2024-12-29T11:10:10.649070image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length60
Median length8
Mean length11.533043
Min length1

Characters and Unicode

Total characters699975
Distinct characters88
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30849 ?
Unique (%)50.8%

Sample

1st row82000027 / 72000159
2nd row82000027 / 72000159
3rd row82000028/72000160
4th row82000030
5th row82000030
ValueCountFrequency (%)
747
 
1.1%
assistenze 313
 
0.5%
rma 305
 
0.5%
materiale 232
 
0.3%
cat 188
 
0.3%
82200355 146
 
0.2%
pack 145
 
0.2%
renove 110
 
0.2%
reso 108
 
0.2%
as06223697 95
 
0.1%
Other values (39470) 63932
96.4%
2024-12-29T11:10:11.080978image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 107823
15.4%
0 98705
14.1%
1 49742
 
7.1%
9 40210
 
5.7%
3 39873
 
5.7%
4 36779
 
5.3%
7 32360
 
4.6%
M 24891
 
3.6%
5 24330
 
3.5%
8 24013
 
3.4%
Other values (78) 221249
31.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 475637
68.0%
Uppercase Letter 190663
27.2%
Dash Punctuation 14672
 
2.1%
Lowercase Letter 6004
 
0.9%
Space Separator 5720
 
0.8%
Other Punctuation 5394
 
0.8%
Connector Punctuation 1675
 
0.2%
Math Symbol 121
 
< 0.1%
Open Punctuation 31
 
< 0.1%
Close Punctuation 31
 
< 0.1%
Other values (3) 27
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 819
13.6%
a 625
10.4%
i 612
10.2%
s 539
9.0%
r 518
8.6%
o 403
 
6.7%
n 378
 
6.3%
t 336
 
5.6%
d 277
 
4.6%
l 265
 
4.4%
Other values (22) 1232
20.5%
Uppercase Letter
ValueCountFrequency (%)
M 24891
13.1%
A 23652
 
12.4%
R 20233
 
10.6%
E 10488
 
5.5%
Z 10131
 
5.3%
V 9706
 
5.1%
L 9324
 
4.9%
P 8129
 
4.3%
W 7160
 
3.8%
N 6604
 
3.5%
Other values (20) 60345
31.7%
Decimal Number
ValueCountFrequency (%)
2 107823
22.7%
0 98705
20.8%
1 49742
10.5%
9 40210
 
8.5%
3 39873
 
8.4%
4 36779
 
7.7%
7 32360
 
6.8%
5 24330
 
5.1%
8 24013
 
5.0%
6 21802
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/ 5157
95.6%
. 147
 
2.7%
, 69
 
1.3%
: 19
 
0.4%
' 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 117
96.7%
> 4
 
3.3%
Other Letter
ValueCountFrequency (%)
º 18
94.7%
ª 1
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 14672
100.0%
Space Separator
ValueCountFrequency (%)
5720
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1675
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
° 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 503289
71.9%
Latin 196686
 
28.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 24891
 
12.7%
A 23652
 
12.0%
R 20233
 
10.3%
E 10488
 
5.3%
Z 10131
 
5.2%
V 9706
 
4.9%
L 9324
 
4.7%
P 8129
 
4.1%
W 7160
 
3.6%
N 6604
 
3.4%
Other values (54) 66368
33.7%
Common
ValueCountFrequency (%)
2 107823
21.4%
0 98705
19.6%
1 49742
9.9%
9 40210
 
8.0%
3 39873
 
7.9%
4 36779
 
7.3%
7 32360
 
6.4%
5 24330
 
4.8%
8 24013
 
4.8%
6 21802
 
4.3%
Other values (14) 27652
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 699879
> 99.9%
None 96
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 107823
15.4%
0 98705
14.1%
1 49742
 
7.1%
9 40210
 
5.7%
3 39873
 
5.7%
4 36779
 
5.3%
7 32360
 
4.6%
M 24891
 
3.6%
5 24330
 
3.5%
8 24013
 
3.4%
Other values (65) 221153
31.6%
None
ValueCountFrequency (%)
à 28
29.2%
ó 20
20.8%
º 18
18.8%
Ó 8
 
8.3%
Á 5
 
5.2%
Í 4
 
4.2%
° 4
 
4.2%
ñ 2
 
2.1%
è 2
 
2.1%
é 2
 
2.1%
Other values (3) 3
 
3.1%
Distinct20136
Distinct (%)43.1%
Missing23679
Missing (%)33.6%
Memory size3.7 MiB
2024-12-29T11:10:11.263771image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length60
Median length8
Mean length8.8150351
Min length1

Characters and Unicode

Total characters412050
Distinct characters76
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10048 ?
Unique (%)21.5%

Sample

1st row62000537
2nd row62000398
3rd row62000398
4th row62000398
5th row62000398
ValueCountFrequency (%)
1912
 
3.6%
fr 948
 
1.8%
alb 218
 
0.4%
fv 193
 
0.4%
ddt 157
 
0.3%
72300828 147
 
0.3%
72300168 97
 
0.2%
reg 79
 
0.1%
72400696 64
 
0.1%
72300047 61
 
0.1%
Other values (20158) 49340
92.7%
2024-12-29T11:10:11.636392image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 85418
20.7%
2 85300
20.7%
7 57221
13.9%
1 36564
8.9%
3 34844
8.5%
4 30700
 
7.5%
6 18674
 
4.5%
5 16325
 
4.0%
8 14127
 
3.4%
9 13965
 
3.4%
Other values (66) 18912
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 393138
95.4%
Space Separator 6597
 
1.6%
Uppercase Letter 6500
 
1.6%
Lowercase Letter 1985
 
0.5%
Other Punctuation 1633
 
0.4%
Dash Punctuation 1404
 
0.3%
Connector Punctuation 657
 
0.2%
Control 71
 
< 0.1%
Math Symbol 59
 
< 0.1%
Other Letter 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1314
20.2%
F 1194
18.4%
E 556
8.6%
A 446
 
6.9%
G 417
 
6.4%
V 355
 
5.5%
D 350
 
5.4%
L 257
 
4.0%
N 256
 
3.9%
T 249
 
3.8%
Other values (16) 1106
17.0%
Lowercase Letter
ValueCountFrequency (%)
a 274
13.8%
l 260
13.1%
e 249
12.5%
d 188
9.5%
b 166
8.4%
r 159
8.0%
o 100
 
5.0%
i 98
 
4.9%
g 95
 
4.8%
n 63
 
3.2%
Other values (15) 333
16.8%
Decimal Number
ValueCountFrequency (%)
0 85418
21.7%
2 85300
21.7%
7 57221
14.6%
1 36564
9.3%
3 34844
8.9%
4 30700
 
7.8%
6 18674
 
4.7%
5 16325
 
4.2%
8 14127
 
3.6%
9 13965
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 1326
81.2%
, 262
 
16.0%
. 19
 
1.2%
; 17
 
1.0%
? 5
 
0.3%
: 4
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 58
98.3%
> 1
 
1.7%
Space Separator
ValueCountFrequency (%)
6597
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1404
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 657
100.0%
Control
ValueCountFrequency (%)
71
100.0%
Other Letter
ValueCountFrequency (%)
º 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 403563
97.9%
Latin 8487
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1314
15.5%
F 1194
 
14.1%
E 556
 
6.6%
A 446
 
5.3%
G 417
 
4.9%
V 355
 
4.2%
D 350
 
4.1%
a 274
 
3.2%
l 260
 
3.1%
L 257
 
3.0%
Other values (42) 3064
36.1%
Common
ValueCountFrequency (%)
0 85418
21.2%
2 85300
21.1%
7 57221
14.2%
1 36564
9.1%
3 34844
8.6%
4 30700
 
7.6%
6 18674
 
4.6%
5 16325
 
4.0%
8 14127
 
3.5%
9 13965
 
3.5%
Other values (14) 10425
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 412046
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 85418
20.7%
2 85300
20.7%
7 57221
13.9%
1 36564
8.9%
3 34844
8.5%
4 30700
 
7.5%
6 18674
 
4.5%
5 16325
 
4.0%
8 14127
 
3.4%
9 13965
 
3.4%
Other values (63) 18908
 
4.6%
None
ValueCountFrequency (%)
º 2
50.0%
ç 1
25.0%
ó 1
25.0%

tipo
Real number (ℝ)

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4433211
Minimum0
Maximum3
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size550.3 KiB
2024-12-29T11:10:11.762485image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile2
Maximum3
Range3
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.53171165
Coefficient of variation (CV)0.36839457
Kurtosis-0.91404197
Mean1.4433211
Median Absolute Deviation (MAD)0
Skewness0.58297771
Sum101643
Variance0.28271728
MonotonicityNot monotonic
2024-12-29T11:10:11.874831image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
1 40456
57.4%
2 28702
40.8%
3 1261
 
1.8%
0 4
 
< 0.1%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 40456
57.4%
2 28702
40.8%
3 1261
 
1.8%
ValueCountFrequency (%)
3 1261
 
1.8%
2 28702
40.8%
1 40456
57.4%
0 4
 
< 0.1%

estado
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.733908
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.3 KiB
2024-12-29T11:10:11.988239image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q16
median6
Q36
95-th percentile76
Maximum76
Range75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.79176
Coefficient of variation (CV)1.6327871
Kurtosis5.3647795
Mean12.733908
Median Absolute Deviation (MAD)0
Skewness2.7128909
Sum896760
Variance432.2973
MonotonicityNot monotonic
2024-12-29T11:10:12.117319image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 60356
85.7%
76 6862
 
9.7%
4 2589
 
3.7%
5 526
 
0.7%
1 54
 
0.1%
2 36
 
0.1%
ValueCountFrequency (%)
1 54
 
0.1%
2 36
 
0.1%
4 2589
 
3.7%
5 526
 
0.7%
6 60356
85.7%
76 6862
 
9.7%
ValueCountFrequency (%)
76 6862
 
9.7%
6 60356
85.7%
5 526
 
0.7%
4 2589
 
3.7%
2 36
 
0.1%
1 54
 
0.1%
Distinct25630
Distinct (%)68.1%
Missing32790
Missing (%)46.6%
Memory size3.4 MiB
2024-12-29T11:10:12.466264image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length70
Median length69
Mean length7.7777217
Min length1

Characters and Unicode

Total characters292699
Distinct characters102
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20767 ?
Unique (%)55.2%

Sample

1st row12459
2nd row1042
3rd row1042
4th row1042
5th row12664
ValueCountFrequency (%)
ticket 1731
 
3.8%
dossier 730
 
1.6%
712
 
1.6%
450
 
1.0%
mario 400
 
0.9%
castillo 399
 
0.9%
eddy 273
 
0.6%
9998 247
 
0.5%
luis 232
 
0.5%
olivo 225
 
0.5%
Other values (25738) 39949
88.1%
2024-12-29T11:10:13.030976image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39471
13.5%
2 31653
10.8%
1 25182
 
8.6%
4 24825
 
8.5%
3 23286
 
8.0%
9 17720
 
6.1%
5 16600
 
5.7%
7 16304
 
5.6%
8 15284
 
5.2%
6 15060
 
5.1%
Other values (92) 67314
23.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 225385
77.0%
Uppercase Letter 43437
 
14.8%
Lowercase Letter 11516
 
3.9%
Space Separator 7787
 
2.7%
Other Symbol 3346
 
1.1%
Other Punctuation 893
 
0.3%
Dash Punctuation 256
 
0.1%
Math Symbol 23
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%
Other values (4) 26
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1467
12.7%
t 1105
 
9.6%
i 1079
 
9.4%
a 894
 
7.8%
c 821
 
7.1%
o 785
 
6.8%
d 680
 
5.9%
n 665
 
5.8%
r 565
 
4.9%
k 458
 
4.0%
Other values (25) 2997
26.0%
Uppercase Letter
ValueCountFrequency (%)
N 4844
11.2%
I 4430
10.2%
E 4349
10.0%
T 4010
9.2%
O 3661
8.4%
S 2996
 
6.9%
A 2898
 
6.7%
R 2695
 
6.2%
C 2522
 
5.8%
L 2143
 
4.9%
Other values (21) 8889
20.5%
Other Punctuation
ValueCountFrequency (%)
* 246
27.5%
. 210
23.5%
/ 183
20.5%
: 112
12.5%
? 68
 
7.6%
, 45
 
5.0%
' 11
 
1.2%
# 6
 
0.7%
· 3
 
0.3%
\ 3
 
0.3%
Other values (5) 6
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 39471
17.5%
2 31653
14.0%
1 25182
11.2%
4 24825
11.0%
3 23286
10.3%
9 17720
7.9%
5 16600
7.4%
7 16304
7.2%
8 15284
 
6.8%
6 15060
 
6.7%
Math Symbol
ValueCountFrequency (%)
+ 22
95.7%
> 1
 
4.3%
Space Separator
ValueCountFrequency (%)
7787
100.0%
Other Symbol
ValueCountFrequency (%)
° 3346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Letter
ValueCountFrequency (%)
º 10
100.0%
Control
ValueCountFrequency (%)
8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Other Number
ValueCountFrequency (%)
² 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 237736
81.2%
Latin 54963
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4844
 
8.8%
I 4430
 
8.1%
E 4349
 
7.9%
T 4010
 
7.3%
O 3661
 
6.7%
S 2996
 
5.5%
A 2898
 
5.3%
R 2695
 
4.9%
C 2522
 
4.6%
L 2143
 
3.9%
Other values (57) 20415
37.1%
Common
ValueCountFrequency (%)
0 39471
16.6%
2 31653
13.3%
1 25182
10.6%
4 24825
10.4%
3 23286
9.8%
9 17720
7.5%
5 16600
7.0%
7 16304
6.9%
8 15284
 
6.4%
6 15060
 
6.3%
Other values (25) 12351
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289229
98.8%
None 3470
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39471
13.6%
2 31653
10.9%
1 25182
 
8.7%
4 24825
 
8.6%
3 23286
 
8.1%
9 17720
 
6.1%
5 16600
 
5.7%
7 16304
 
5.6%
8 15284
 
5.3%
6 15060
 
5.2%
Other values (74) 63844
22.1%
None
ValueCountFrequency (%)
° 3346
96.4%
é 75
 
2.2%
º 10
 
0.3%
Ñ 9
 
0.3%
è 4
 
0.1%
É 4
 
0.1%
· 3
 
0.1%
ú 3
 
0.1%
² 3
 
0.1%
ó 3
 
0.1%
Other values (8) 10
 
0.3%

dire_envio_id
Real number (ℝ)

Distinct8696
Distinct (%)20.2%
Missing27434
Missing (%)39.0%
Infinite0
Infinite (%)0.0%
Mean8921.0796
Minimum54
Maximum23447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:13.193338image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile688
Q14511
median7928
Q312453
95-th percentile20516
Maximum23447
Range23393
Interquartile range (IQR)7942

Descriptive statistics

Standard deviation5958.7585
Coefficient of variation (CV)0.66794142
Kurtosis-0.51078463
Mean8921.0796
Median Absolute Deviation (MAD)3926
Skewness0.55567263
Sum3.8350829 × 108
Variance35506803
MonotonicityNot monotonic
2024-12-29T11:10:13.345876image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10230 517
 
0.7%
5735 499
 
0.7%
9458 416
 
0.6%
7090 340
 
0.5%
2214 315
 
0.4%
4514 313
 
0.4%
6192 311
 
0.4%
4511 295
 
0.4%
2018 290
 
0.4%
2610 283
 
0.4%
Other values (8686) 39410
56.0%
(Missing) 27434
39.0%
ValueCountFrequency (%)
54 1
 
< 0.1%
55 6
 
< 0.1%
59 79
0.1%
72 39
0.1%
80 11
 
< 0.1%
87 2
 
< 0.1%
100 3
 
< 0.1%
105 1
 
< 0.1%
147 4
 
< 0.1%
158 3
 
< 0.1%
ValueCountFrequency (%)
23447 1
< 0.1%
23441 1
< 0.1%
23440 1
< 0.1%
23439 1
< 0.1%
23438 1
< 0.1%
23437 2
< 0.1%
23436 1
< 0.1%
23435 1
< 0.1%
23432 1
< 0.1%
23428 1
< 0.1%

dire_recogida_id
Real number (ℝ)

Distinct5862
Distinct (%)13.4%
Missing26779
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean8295.192
Minimum59
Maximum24230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:13.502533image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum59
5-th percentile688
Q13082
median7501.5
Q311833.25
95-th percentile19735
Maximum24230
Range24171
Interquartile range (IQR)8751.25

Descriptive statistics

Standard deviation5836.2463
Coefficient of variation (CV)0.70356977
Kurtosis-0.45180512
Mean8295.192
Median Absolute Deviation (MAD)4381.5
Skewness0.5793643
Sum3.6203536 × 108
Variance34061771
MonotonicityNot monotonic
2024-12-29T11:10:13.672863image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2018 1344
 
1.9%
844 714
 
1.0%
2214 634
 
0.9%
7090 506
 
0.7%
9458 460
 
0.7%
14000 428
 
0.6%
6192 411
 
0.6%
5741 385
 
0.5%
10345 343
 
0.5%
10230 327
 
0.5%
Other values (5852) 38092
54.1%
(Missing) 26779
38.0%
ValueCountFrequency (%)
59 77
 
0.1%
72 54
 
0.1%
80 5
 
< 0.1%
87 3
 
< 0.1%
100 2
 
< 0.1%
105 3
 
< 0.1%
158 7
 
< 0.1%
160 31
 
< 0.1%
163 315
0.4%
166 1
 
< 0.1%
ValueCountFrequency (%)
24230 1
< 0.1%
24198 1
< 0.1%
24017 1
< 0.1%
23998 2
< 0.1%
23845 1
< 0.1%
23830 1
< 0.1%
23797 1
< 0.1%
23743 1
< 0.1%
23742 1
< 0.1%
23728 1
< 0.1%

peso3
Real number (ℝ)

Distinct495
Distinct (%)1.2%
Missing28236
Missing (%)40.1%
Infinite0
Infinite (%)0.0%
Mean9.0176633
Minimum0.01
Maximum200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.3 KiB
2024-12-29T11:10:13.832916image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.32
Q11
median1
Q33
95-th percentile12.01
Maximum200000
Range199999.99
Interquartile range (IQR)2

Descriptive statistics

Standard deviation974.1464
Coefficient of variation (CV)108.02648
Kurtosis42112.133
Mean9.0176633
Median Absolute Deviation (MAD)0.5
Skewness205.12259
Sum380428.16
Variance948961.21
MonotonicityNot monotonic
2024-12-29T11:10:14.005178image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 15745
22.4%
2 6618
 
9.4%
3 3071
 
4.4%
0.5 3027
 
4.3%
5 2026
 
2.9%
1.5 1003
 
1.4%
4 812
 
1.2%
0.2 769
 
1.1%
10 736
 
1.0%
0.3 557
 
0.8%
Other values (485) 7823
 
11.1%
(Missing) 28236
40.1%
ValueCountFrequency (%)
0.01 94
 
0.1%
0.02 7
 
< 0.1%
0.03 6
 
< 0.1%
0.04 3
 
< 0.1%
0.05 22
 
< 0.1%
0.06 1
 
< 0.1%
0.07 3
 
< 0.1%
0.1 244
0.3%
0.11 1
 
< 0.1%
0.111 1
 
< 0.1%
ValueCountFrequency (%)
200000 1
 
< 0.1%
2130 2
 
< 0.1%
1752 5
< 0.1%
1060 1
 
< 0.1%
700 2
 
< 0.1%
500 4
< 0.1%
450 2
 
< 0.1%
400 2
 
< 0.1%
360 5
< 0.1%
342 7
< 0.1%

volumen3
Real number (ℝ)

Distinct4
Distinct (%)80.0%
Missing70418
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean55101534
Minimum7200571
Maximum72200409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size550.3 KiB
2024-12-29T11:10:14.136134image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum7200571
5-th percentile18160983
Q162002632
median62002632
Q372101427
95-th percentile72180613
Maximum72200409
Range64999838
Interquartile range (IQR)10098795

Descriptive statistics

Standard deviation27253993
Coefficient of variation (CV)0.49461404
Kurtosis4.3211375
Mean55101534
Median Absolute Deviation (MAD)10098795
Skewness-2.0446544
Sum2.7550767 × 108
Variance7.4278011 × 1014
MonotonicityNot monotonic
2024-12-29T11:10:14.248400image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
62002632 2
 
< 0.1%
72101427 1
 
< 0.1%
72200409 1
 
< 0.1%
7200571 1
 
< 0.1%
(Missing) 70418
> 99.9%
ValueCountFrequency (%)
7200571 1
< 0.1%
62002632 2
< 0.1%
72101427 1
< 0.1%
72200409 1
< 0.1%
ValueCountFrequency (%)
72200409 1
< 0.1%
72101427 1
< 0.1%
62002632 2
< 0.1%
7200571 1
< 0.1%

estadofr
Real number (ℝ)

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4759667
Minimum0
Maximum44
Zeros8624
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:14.381531image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q34
95-th percentile43
Maximum44
Range44
Interquartile range (IQR)3

Descriptive statistics

Standard deviation12.408866
Coefficient of variation (CV)1.9161412
Kurtosis3.6285232
Mean6.4759667
Median Absolute Deviation (MAD)1
Skewness2.3056026
Sum456057
Variance153.97996
MonotonicityNot monotonic
2024-12-29T11:10:14.515413image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 33715
47.9%
4 16371
23.2%
0 8624
 
12.2%
43 4043
 
5.7%
38 1350
 
1.9%
40 929
 
1.3%
25 902
 
1.3%
5 847
 
1.2%
37 764
 
1.1%
3 569
 
0.8%
Other values (21) 2309
 
3.3%
ValueCountFrequency (%)
0 8624
 
12.2%
1 33715
47.9%
2 222
 
0.3%
3 569
 
0.8%
4 16371
23.2%
5 847
 
1.2%
6 462
 
0.7%
7 20
 
< 0.1%
9 13
 
< 0.1%
10 10
 
< 0.1%
ValueCountFrequency (%)
44 1
 
< 0.1%
43 4043
5.7%
42 215
 
0.3%
41 30
 
< 0.1%
40 929
 
1.3%
39 135
 
0.2%
38 1350
 
1.9%
37 764
 
1.1%
26 1
 
< 0.1%
25 902
 
1.3%

c_mail
Text

Distinct638
Distinct (%)22.5%
Missing67591
Missing (%)96.0%
Memory size2.3 MiB
2024-12-29T11:10:14.780816image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length46
Median length36
Mean length23.868291
Min length2

Characters and Unicode

Total characters67595
Distinct characters74
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)12.5%

Sample

1st rowrdorde@airzonefrance.fr
2nd rowt.ramos@suministradora.com
3rd rowt.ramos@suministradora.com
4th rowguillaume.druelle@dalkia.fr
5th rowguillaume.druelle@dalkia.fr
ValueCountFrequency (%)
eaunette@airzonefrance.fr 385
 
13.4%
pjmorales@airzone.es 104
 
3.6%
t.ramos@suministradora.com 90
 
3.1%
ruth.formigo@sonepar.es 90
 
3.1%
cfernandez@airzone.es 78
 
2.7%
juandaniel.padilla@sonepar.es 75
 
2.6%
abermudo@airzone.es 74
 
2.6%
jscapiali@airzonefrance.fr 74
 
2.6%
rdorde@airzonefrance.fr 70
 
2.4%
gabriel.carrillo@sonepar.es 60
 
2.1%
Other values (606) 1771
61.7%
2024-12-29T11:10:15.216681image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5822
 
8.6%
e 5362
 
7.9%
r 5245
 
7.8%
o 4989
 
7.4%
i 4200
 
6.2%
n 4069
 
6.0%
. 3472
 
5.1%
c 3019
 
4.5%
@ 2814
 
4.2%
s 2798
 
4.1%
Other values (64) 25805
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51296
75.9%
Uppercase Letter 9642
 
14.3%
Other Punctuation 6293
 
9.3%
Decimal Number 234
 
0.3%
Dash Punctuation 70
 
0.1%
Space Separator 39
 
0.1%
Math Symbol 20
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5822
11.3%
e 5362
10.5%
r 5245
10.2%
o 4989
9.7%
i 4200
 
8.2%
n 4069
 
7.9%
c 3019
 
5.9%
s 2798
 
5.5%
m 2610
 
5.1%
l 2317
 
4.5%
Other values (20) 10865
21.2%
Uppercase Letter
ValueCountFrequency (%)
E 1774
18.4%
R 1036
10.7%
A 1005
10.4%
N 1003
10.4%
O 659
 
6.8%
I 581
 
6.0%
C 535
 
5.5%
F 503
 
5.2%
T 494
 
5.1%
S 347
 
3.6%
Other values (15) 1705
17.7%
Decimal Number
ValueCountFrequency (%)
0 56
23.9%
1 53
22.6%
2 40
17.1%
3 20
 
8.5%
7 18
 
7.7%
8 14
 
6.0%
6 10
 
4.3%
5 10
 
4.3%
4 9
 
3.8%
9 4
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 3472
55.2%
@ 2814
44.7%
; 6
 
0.1%
, 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
< 10
50.0%
> 10
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60938
90.2%
Common 6657
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5822
 
9.6%
e 5362
 
8.8%
r 5245
 
8.6%
o 4989
 
8.2%
i 4200
 
6.9%
n 4069
 
6.7%
c 3019
 
5.0%
s 2798
 
4.6%
m 2610
 
4.3%
l 2317
 
3.8%
Other values (45) 20507
33.7%
Common
ValueCountFrequency (%)
. 3472
52.2%
@ 2814
42.3%
- 70
 
1.1%
0 56
 
0.8%
1 53
 
0.8%
2 40
 
0.6%
39
 
0.6%
3 20
 
0.3%
7 18
 
0.3%
8 14
 
0.2%
Other values (9) 61
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67574
> 99.9%
None 21
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5822
 
8.6%
e 5362
 
7.9%
r 5245
 
7.8%
o 4989
 
7.4%
i 4200
 
6.2%
n 4069
 
6.0%
. 3472
 
5.1%
c 3019
 
4.5%
@ 2814
 
4.2%
s 2798
 
4.1%
Other values (60) 25784
38.2%
None
ValueCountFrequency (%)
ñ 9
42.9%
ú 8
38.1%
é 3
 
14.3%
á 1
 
4.8%

c_tel
Text

Distinct909
Distinct (%)28.2%
Missing67202
Missing (%)95.4%
Memory size2.3 MiB
2024-12-29T11:10:15.513007image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length38
Median length33
Mean length10.616889
Min length1

Characters and Unicode

Total characters34197
Distinct characters71
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique558 ?
Unique (%)17.3%

Sample

1st row0684541105
2nd row937206363
3rd row937206363
4th row629 03 09 16
5th row610 403 103
ValueCountFrequency (%)
0631683163 356
 
7.3%
961223300 159
 
3.3%
683242387 149
 
3.1%
687805455 128
 
2.6%
937206363 106
 
2.2%
0680849660 76
 
1.6%
0684541105 70
 
1.4%
79 70
 
1.4%
680479813 69
 
1.4%
667 63
 
1.3%
Other values (988) 3636
74.5%
2024-12-29T11:10:16.005132image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 4897
14.3%
0 3333
9.7%
3 3330
9.7%
8 2820
 
8.2%
2 2356
 
6.9%
1 2308
 
6.7%
7 2159
 
6.3%
5 2149
 
6.3%
9 1956
 
5.7%
4 1790
 
5.2%
Other values (61) 7099
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27098
79.2%
Uppercase Letter 5020
 
14.7%
Space Separator 1671
 
4.9%
Lowercase Letter 235
 
0.7%
Other Punctuation 124
 
0.4%
Math Symbol 39
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 711
14.2%
E 515
10.3%
O 499
9.9%
N 450
9.0%
R 434
 
8.6%
I 377
 
7.5%
L 261
 
5.2%
D 251
 
5.0%
S 232
 
4.6%
U 179
 
3.6%
Other values (17) 1111
22.1%
Lowercase Letter
ValueCountFrequency (%)
a 33
14.0%
e 30
12.8%
r 23
 
9.8%
o 17
 
7.2%
i 15
 
6.4%
u 13
 
5.5%
l 12
 
5.1%
x 12
 
5.1%
s 11
 
4.7%
n 10
 
4.3%
Other values (13) 59
25.1%
Decimal Number
ValueCountFrequency (%)
6 4897
18.1%
0 3333
12.3%
3 3330
12.3%
8 2820
10.4%
2 2356
8.7%
1 2308
8.5%
7 2159
8.0%
5 2149
7.9%
9 1956
 
7.2%
4 1790
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 110
88.7%
/ 12
 
9.7%
: 1
 
0.8%
@ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
1660
99.3%
  11
 
0.7%
Math Symbol
ValueCountFrequency (%)
+ 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28942
84.6%
Latin 5255
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 711
13.5%
E 515
 
9.8%
O 499
 
9.5%
N 450
 
8.6%
R 434
 
8.3%
I 377
 
7.2%
L 261
 
5.0%
D 251
 
4.8%
S 232
 
4.4%
U 179
 
3.4%
Other values (40) 1346
25.6%
Common
ValueCountFrequency (%)
6 4897
16.9%
0 3333
11.5%
3 3330
11.5%
8 2820
9.7%
2 2356
8.1%
1 2308
8.0%
7 2159
7.5%
5 2149
7.4%
9 1956
 
6.8%
4 1790
 
6.2%
Other values (11) 1844
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34180
> 99.9%
None 17
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 4897
14.3%
0 3333
9.8%
3 3330
9.7%
8 2820
 
8.3%
2 2356
 
6.9%
1 2308
 
6.8%
7 2159
 
6.3%
5 2149
 
6.3%
9 1956
 
5.7%
4 1790
 
5.2%
Other values (58) 7082
20.7%
None
ValueCountFrequency (%)
  11
64.7%
Ñ 3
 
17.6%
ñ 3
 
17.6%

c_obs
Text

Distinct1067
Distinct (%)48.7%
Missing68233
Missing (%)96.9%
Memory size2.6 MiB
2024-12-29T11:10:16.300920image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length2219
Median length488
Mean length121.13151
Min length1

Characters and Unicode

Total characters265278
Distinct characters114
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique718 ?
Unique (%)32.8%

Sample

1st rowRAS
2nd rowTERMOSTATO EN GARANTIA NO FUNCIONA --
3rd rowTERMOSTATO NO FUNCIONA, MATERIAL EN GARANTIA --
4th rowQUANTITE A ENVOYER 2 X AZZS6IBPRO6E 2 X AZX6010VOLTZ
5th rowQUANTITE A ENVOYER 2 X AZZS6IBPRO6E 2 X AZX6010VOLTZ
ValueCountFrequency (%)
de 1371
 
3.2%
se 1229
 
2.9%
1177
 
2.7%
que 987
 
2.3%
en 943
 
2.2%
a 843
 
2.0%
el 827
 
1.9%
y 746
 
1.7%
por 660
 
1.5%
la 648
 
1.5%
Other values (4777) 33408
78.0%
2024-12-29T11:10:16.766399image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39062
 
14.7%
E 17966
 
6.8%
A 17049
 
6.4%
O 11620
 
4.4%
R 10117
 
3.8%
N 9749
 
3.7%
I 9359
 
3.5%
L 7585
 
2.9%
C 7357
 
2.8%
0 7117
 
2.7%
Other values (104) 128297
48.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 141427
53.3%
Lowercase Letter 52032
 
19.6%
Space Separator 39065
 
14.7%
Decimal Number 18722
 
7.1%
Control 6815
 
2.6%
Other Punctuation 5394
 
2.0%
Dash Punctuation 949
 
0.4%
Open Punctuation 296
 
0.1%
Close Punctuation 286
 
0.1%
Math Symbol 126
 
< 0.1%
Other values (4) 166
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7005
13.5%
a 5576
10.7%
o 4161
 
8.0%
r 4068
 
7.8%
n 3924
 
7.5%
i 3688
 
7.1%
l 3183
 
6.1%
s 2747
 
5.3%
t 2682
 
5.2%
d 2236
 
4.3%
Other values (27) 12762
24.5%
Uppercase Letter
ValueCountFrequency (%)
E 17966
12.7%
A 17049
12.1%
O 11620
 
8.2%
R 10117
 
7.2%
N 9749
 
6.9%
I 9359
 
6.6%
L 7585
 
5.4%
C 7357
 
5.2%
S 7060
 
5.0%
D 6677
 
4.7%
Other values (25) 36888
26.1%
Other Punctuation
ValueCountFrequency (%)
, 2348
43.5%
. 2075
38.5%
: 319
 
5.9%
' 224
 
4.2%
/ 97
 
1.8%
? 96
 
1.8%
* 95
 
1.8%
\ 44
 
0.8%
% 25
 
0.5%
@ 22
 
0.4%
Other values (5) 49
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 7117
38.0%
1 2850
15.2%
2 2386
 
12.7%
6 1447
 
7.7%
5 1069
 
5.7%
3 958
 
5.1%
4 825
 
4.4%
9 752
 
4.0%
8 720
 
3.8%
7 598
 
3.2%
Math Symbol
ValueCountFrequency (%)
+ 94
74.6%
> 22
 
17.5%
< 8
 
6.3%
= 1
 
0.8%
| 1
 
0.8%
Control
ValueCountFrequency (%)
3209
47.1%
3209
47.1%
397
 
5.8%
Space Separator
ValueCountFrequency (%)
39062
> 99.9%
  3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 949
100.0%
Open Punctuation
ValueCountFrequency (%)
( 296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Other Letter
ValueCountFrequency (%)
º 123
100.0%
Other Symbol
ValueCountFrequency (%)
° 38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 193582
73.0%
Common 71696
 
27.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 17966
 
9.3%
A 17049
 
8.8%
O 11620
 
6.0%
R 10117
 
5.2%
N 9749
 
5.0%
I 9359
 
4.8%
L 7585
 
3.9%
C 7357
 
3.8%
S 7060
 
3.6%
e 7005
 
3.6%
Other values (63) 88715
45.8%
Common
ValueCountFrequency (%)
39062
54.5%
0 7117
 
9.9%
3209
 
4.5%
3209
 
4.5%
1 2850
 
4.0%
2 2386
 
3.3%
, 2348
 
3.3%
. 2075
 
2.9%
6 1447
 
2.0%
5 1069
 
1.5%
Other values (31) 6924
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 263944
99.5%
None 1334
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39062
 
14.8%
E 17966
 
6.8%
A 17049
 
6.5%
O 11620
 
4.4%
R 10117
 
3.8%
N 9749
 
3.7%
I 9359
 
3.5%
L 7585
 
2.9%
C 7357
 
2.8%
0 7117
 
2.7%
Other values (78) 126963
48.1%
None
ValueCountFrequency (%)
é 481
36.1%
Ó 153
 
11.5%
ó 148
 
11.1%
º 123
 
9.2%
í 80
 
6.0%
à 52
 
3.9%
Ñ 49
 
3.7%
á 47
 
3.5%
Í 39
 
2.9%
° 38
 
2.8%
Other values (16) 124
 
9.3%
Distinct2
Distinct (%)< 0.1%
Missing62173
Missing (%)88.3%
Memory size2.4 MiB
2024-12-29T11:10:16.903701image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters66000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaccepted
2nd rowaccepted
3rd rownotified
4th rownotified
5th rownotified
ValueCountFrequency (%)
accepted 5979
72.5%
notified 2271
 
27.5%
2024-12-29T11:10:17.145248image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14229
21.6%
c 11958
18.1%
t 8250
12.5%
d 8250
12.5%
a 5979
9.1%
p 5979
9.1%
i 4542
 
6.9%
n 2271
 
3.4%
o 2271
 
3.4%
f 2271
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66000
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14229
21.6%
c 11958
18.1%
t 8250
12.5%
d 8250
12.5%
a 5979
9.1%
p 5979
9.1%
i 4542
 
6.9%
n 2271
 
3.4%
o 2271
 
3.4%
f 2271
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 66000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14229
21.6%
c 11958
18.1%
t 8250
12.5%
d 8250
12.5%
a 5979
9.1%
p 5979
9.1%
i 4542
 
6.9%
n 2271
 
3.4%
o 2271
 
3.4%
f 2271
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14229
21.6%
c 11958
18.1%
t 8250
12.5%
d 8250
12.5%
a 5979
9.1%
p 5979
9.1%
i 4542
 
6.9%
n 2271
 
3.4%
o 2271
 
3.4%
f 2271
 
3.4%
Distinct35485
Distinct (%)54.0%
Missing4741
Missing (%)6.7%
Memory size11.8 MiB
2024-12-29T11:10:17.448385image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length500
Median length458
Mean length76.620566
Min length1

Characters and Unicode

Total characters5032592
Distinct characters149
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26437 ?
Unique (%)40.2%

Sample

1st rowSolicitamos cambio de termostatos cables a termostatos inalámbricos.
2nd rowSolicitamos cambio de termostatos cables a termostatos inalámbricos.
3rd rowNECESITAMOS QUE NOS ENVIEN 1 TERMOSTATO AZRA6LITERB, NO HAY POSIBLILIDAD DE PONERLO CABLE
4th rowSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ. APARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.
5th rowSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ. APARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.
ValueCountFrequency (%)
de 32333
 
4.1%
la 17266
 
2.2%
el 14448
 
1.8%
no 13188
 
1.7%
en 12768
 
1.6%
se 11316
 
1.4%
que 10942
 
1.4%
y 10933
 
1.4%
10859
 
1.4%
por 8674
 
1.1%
Other values (40290) 647129
81.9%
2024-12-29T11:10:17.957177image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
711823
 
14.1%
e 278695
 
5.5%
E 234207
 
4.7%
a 207341
 
4.1%
A 199227
 
4.0%
o 180423
 
3.6%
n 158031
 
3.1%
O 154969
 
3.1%
i 148822
 
3.0%
r 145147
 
2.9%
Other values (139) 2613907
51.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2061385
41.0%
Uppercase Letter 1838341
36.5%
Space Separator 711833
 
14.1%
Decimal Number 254139
 
5.0%
Other Punctuation 79458
 
1.6%
Control 60185
 
1.2%
Dash Punctuation 9276
 
0.2%
Open Punctuation 4408
 
0.1%
Close Punctuation 4345
 
0.1%
Other Symbol 4078
 
0.1%
Other values (7) 5144
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 278695
13.5%
a 207341
10.1%
o 180423
 
8.8%
n 158031
 
7.7%
i 148822
 
7.2%
r 145147
 
7.0%
t 129243
 
6.3%
s 124784
 
6.1%
l 117440
 
5.7%
c 91850
 
4.5%
Other values (38) 479609
23.3%
Uppercase Letter
ValueCountFrequency (%)
E 234207
12.7%
A 199227
10.8%
O 154969
 
8.4%
N 140570
 
7.6%
R 129571
 
7.0%
I 126667
 
6.9%
T 108108
 
5.9%
S 104269
 
5.7%
L 100892
 
5.5%
C 91479
 
5.0%
Other values (36) 448382
24.4%
Other Punctuation
ValueCountFrequency (%)
. 35996
45.3%
, 20703
26.1%
/ 6583
 
8.3%
: 5543
 
7.0%
' 5272
 
6.6%
\ 1955
 
2.5%
? 1399
 
1.8%
" 665
 
0.8%
* 390
 
0.5%
; 235
 
0.3%
Other values (8) 717
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 52659
20.7%
2 45526
17.9%
1 38393
15.1%
3 22716
8.9%
6 22230
8.7%
4 19869
 
7.8%
5 16756
 
6.6%
8 12869
 
5.1%
7 12089
 
4.8%
9 11032
 
4.3%
Math Symbol
ValueCountFrequency (%)
+ 1507
74.6%
> 293
 
14.5%
= 164
 
8.1%
< 52
 
2.6%
| 3
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 13
68.4%
` 4
 
21.1%
¨ 1
 
5.3%
^ 1
 
5.3%
Control
ValueCountFrequency (%)
29678
49.3%
29661
49.3%
846
 
1.4%
Space Separator
ValueCountFrequency (%)
711823
> 99.9%
  10
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4399
99.8%
[ 9
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 4337
99.8%
] 8
 
0.2%
Other Letter
ValueCountFrequency (%)
º 1735
93.8%
ª 115
 
6.2%
Currency Symbol
ValueCountFrequency (%)
£ 1
50.0%
$ 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 9276
100.0%
Other Symbol
ValueCountFrequency (%)
° 4078
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1211
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 22
100.0%
Final Punctuation
ValueCountFrequency (%)
» 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3901576
77.5%
Common 1131016
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 278695
 
7.1%
E 234207
 
6.0%
a 207341
 
5.3%
A 199227
 
5.1%
o 180423
 
4.6%
n 158031
 
4.1%
O 154969
 
4.0%
i 148822
 
3.8%
r 145147
 
3.7%
N 140570
 
3.6%
Other values (86) 2054144
52.6%
Common
ValueCountFrequency (%)
711823
62.9%
0 52659
 
4.7%
2 45526
 
4.0%
1 38393
 
3.4%
. 35996
 
3.2%
29678
 
2.6%
29661
 
2.6%
3 22716
 
2.0%
6 22230
 
2.0%
, 20703
 
1.8%
Other values (43) 121631
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4981667
99.0%
None 50925
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
711823
 
14.3%
e 278695
 
5.6%
E 234207
 
4.7%
a 207341
 
4.2%
A 199227
 
4.0%
o 180423
 
3.6%
n 158031
 
3.2%
O 154969
 
3.1%
i 148822
 
3.0%
r 145147
 
2.9%
Other values (85) 2562982
51.4%
None
ValueCountFrequency (%)
é 17293
34.0%
ó 7025
13.8%
° 4078
 
8.0%
Ó 3362
 
6.6%
è 3222
 
6.3%
í 3160
 
6.2%
á 2243
 
4.4%
à 1966
 
3.9%
º 1735
 
3.4%
ú 926
 
1.8%
Other values (44) 5915
 
11.6%
Distinct43757
Distinct (%)63.4%
Missing1426
Missing (%)2.0%
Memory size4.5 MiB
2024-12-29T11:10:18.210611image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters689970
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35299 ?
Unique (%)51.2%

Sample

1st rowMGHQM2LT55
2nd rowMGHQM2LT55
3rd rowLMPOM2TR8B
4th rowLMNWLG1U1A
5th rowLMNWLG1U1A
ValueCountFrequency (%)
bgvjymat77 146
 
0.2%
m5iwmzznd9 95
 
0.1%
m2dqbgdm0b 64
 
0.1%
am9pa21s32 60
 
0.1%
ljqcmz1m00 59
 
0.1%
b29ozmzv3e 57
 
0.1%
m5ebm5dj2f 57
 
0.1%
y2plz2ky3a 56
 
0.1%
k2lrmg5r5b 56
 
0.1%
njgel5plb9 50
 
0.1%
Other values (43747) 68297
99.0%
2024-12-29T11:10:18.603495image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 61365
 
8.9%
Z 46761
 
6.8%
A 40354
 
5.8%
L 40103
 
5.8%
2 34821
 
5.0%
W 34546
 
5.0%
G 31684
 
4.6%
P 28486
 
4.1%
N 27430
 
4.0%
B 25485
 
3.7%
Other values (26) 318935
46.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 556450
80.6%
Decimal Number 133520
 
19.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 61365
 
11.0%
Z 46761
 
8.4%
A 40354
 
7.3%
L 40103
 
7.2%
W 34546
 
6.2%
G 31684
 
5.7%
P 28486
 
5.1%
N 27430
 
4.9%
B 25485
 
4.6%
D 21131
 
3.8%
Other values (16) 199105
35.8%
Decimal Number
ValueCountFrequency (%)
2 34821
26.1%
5 20600
15.4%
1 15264
11.4%
9 10554
 
7.9%
3 9019
 
6.8%
0 8864
 
6.6%
4 8753
 
6.6%
7 8605
 
6.4%
8 8587
 
6.4%
6 8453
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 556450
80.6%
Common 133520
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 61365
 
11.0%
Z 46761
 
8.4%
A 40354
 
7.3%
L 40103
 
7.2%
W 34546
 
6.2%
G 31684
 
5.7%
P 28486
 
5.1%
N 27430
 
4.9%
B 25485
 
4.6%
D 21131
 
3.8%
Other values (16) 199105
35.8%
Common
ValueCountFrequency (%)
2 34821
26.1%
5 20600
15.4%
1 15264
11.4%
9 10554
 
7.9%
3 9019
 
6.8%
0 8864
 
6.6%
4 8753
 
6.6%
7 8605
 
6.4%
8 8587
 
6.4%
6 8453
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 689970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 61365
 
8.9%
Z 46761
 
6.8%
A 40354
 
5.8%
L 40103
 
5.8%
2 34821
 
5.0%
W 34546
 
5.0%
G 31684
 
4.6%
P 28486
 
4.1%
N 27430
 
4.0%
B 25485
 
3.7%
Other values (26) 318935
46.2%

id_pieza
Real number (ℝ)

 Raw Dataset ProfilePreprocessed Dataset Profile
Distinct6899719359
Distinct (%)100.0%100.0%
Missing14260
Missing (%)2.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean65749.7758385.782
 Raw Dataset ProfilePreprocessed Dataset Profile
Minimum2946329479
Maximum10185493099
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size619.1 KiB170.3 KiB
2024-12-29T11:10:18.796364image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

 Raw Dataset ProfilePreprocessed Dataset Profile
Minimum2946329479
5-th percentile33072.832675.7
Q14770943363.5
median6573357214
Q38391773007
95-th percentile98274.287519
Maximum10185493099
Range7239163620
Interquartile range (IQR)3620829643.5

Descriptive statistics

 Raw Dataset ProfilePreprocessed Dataset Profile
Standard deviation20904.2217538.026
Coefficient of variation (CV)0.317936020.30038179
Kurtosis-1.1987341-1.1380243
Mean65749.7758385.782
Median Absolute Deviation (MAD)1810414589
Skewness-0.00401489510.17137332
Sum4.5365369 × 1091.1302904 × 109
Variance4.3698642 × 1083.0758235 × 108
MonotonicityNot monotonicNot monotonic
2024-12-29T11:10:19.261657image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77835 1
 
< 0.1%
77816 1
 
< 0.1%
77822 1
 
< 0.1%
77823 1
 
< 0.1%
77824 1
 
< 0.1%
77826 1
 
< 0.1%
77825 1
 
< 0.1%
77827 1
 
< 0.1%
77828 1
 
< 0.1%
77829 1
 
< 0.1%
Other values (68987) 68987
98.0%
(Missing) 1426
 
2.0%
ValueCountFrequency (%)
29479 1
 
< 0.1%
67592 1
 
< 0.1%
67585 1
 
< 0.1%
67584 1
 
< 0.1%
67578 1
 
< 0.1%
67575 1
 
< 0.1%
67573 1
 
< 0.1%
67572 1
 
< 0.1%
67569 1
 
< 0.1%
67568 1
 
< 0.1%
Other values (19349) 19349
99.9%
ValueCountFrequency (%)
29463 1
< 0.1%
29464 1
< 0.1%
29465 1
< 0.1%
29466 1
< 0.1%
29467 1
< 0.1%
29468 1
< 0.1%
29469 1
< 0.1%
29470 1
< 0.1%
29471 1
< 0.1%
29472 1
< 0.1%
ValueCountFrequency (%)
29479 1
< 0.1%
29480 1
< 0.1%
29481 1
< 0.1%
29482 1
< 0.1%
29487 1
< 0.1%
29490 1
< 0.1%
29491 1
< 0.1%
29492 1
< 0.1%
29493 1
< 0.1%
29522 1
< 0.1%
ValueCountFrequency (%)
29479 1
< 0.1%
29480 1
< 0.1%
29481 1
< 0.1%
29482 1
< 0.1%
29487 1
< 0.1%
29490 1
< 0.1%
29491 1
< 0.1%
29492 1
< 0.1%
29493 1
< 0.1%
29522 1
< 0.1%
ValueCountFrequency (%)
29463 1
< 0.1%
29464 1
< 0.1%
29465 1
< 0.1%
29466 1
< 0.1%
29467 1
< 0.1%
29468 1
< 0.1%
29469 1
< 0.1%
29470 1
< 0.1%
29471 1
< 0.1%
29472 1
< 0.1%

user_id_pieza
Real number (ℝ)

Distinct4169
Distinct (%)6.0%
Missing1426
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean3602.3952
Minimum0
Maximum10939
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:19.439670image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile118
Q1668
median3299
Q35853
95-th percentile8852
Maximum10939
Range10939
Interquartile range (IQR)5185

Descriptive statistics

Standard deviation2900.5
Coefficient of variation (CV)0.80515874
Kurtosis-0.85824229
Mean3602.3952
Median Absolute Deviation (MAD)2606
Skewness0.49060378
Sum2.4855446 × 108
Variance8412900.1
MonotonicityNot monotonic
2024-12-29T11:10:19.603305image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3656 2694
 
3.8%
110 1369
 
1.9%
136 986
 
1.4%
1531 894
 
1.3%
4168 863
 
1.2%
504 753
 
1.1%
145 749
 
1.1%
471 696
 
1.0%
7604 675
 
1.0%
4396 648
 
0.9%
Other values (4159) 58670
83.3%
(Missing) 1426
 
2.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
2 5
 
< 0.1%
3 4
 
< 0.1%
25 71
0.1%
29 7
 
< 0.1%
59 5
 
< 0.1%
69 13
 
< 0.1%
70 1
 
< 0.1%
71 10
 
< 0.1%
72 2
 
< 0.1%
ValueCountFrequency (%)
10939 1
< 0.1%
10938 1
< 0.1%
10936 2
< 0.1%
10931 1
< 0.1%
10930 1
< 0.1%
10923 1
< 0.1%
10922 1
< 0.1%
10921 1
< 0.1%
10920 1
< 0.1%
10915 1
< 0.1%

cod_articulo
['Text', 'Text']

 Raw Dataset ProfilePreprocessed Dataset Profile
Distinct106092397
Distinct (%)15.4%12.4%
Missing14350
Missing (%)2.0%0.0%
Memory size4.6 MiB1.3 MiB
2024-12-29T11:10:20.003314image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

 Raw Dataset ProfilePreprocessed Dataset Profile
Max length1616
Median length1414
Mean length11.70641312.181776
Min length11

Characters and Unicode

 Raw Dataset ProfilePreprocessed Dataset Profile
Total characters807602235827
Distinct characters10282
Distinct categories1514 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Raw Dataset ProfilePreprocessed Dataset Profile
Unique74631606 ?
Unique (%)10.8%8.3%

Sample

 Raw Dataset ProfilePreprocessed Dataset Profile
1st rowAZCE6BLUEFACECBAZXWSCLOUDWIFI
2nd rowAZCE6LITECBAZX6QADAPTHIT
3rd rowAZRA6LITECBAZX6QADAPTHIT
4th rowAZX6QADAPTSAMAZX6CCP
5th rowAZX6QADAPTSAMAZCE6EXP8Z
ValueCountFrequency (%)
azce6thinkrb 5386
 
7.1%
azpv8cb1iaq 2470
 
3.3%
azce6bluefacecb 2349
 
3.1%
azce6bluezerocb 2049
 
2.7%
azx6wsc5ger 1773
 
2.3%
azce6flexa3 1086
 
1.4%
azx6wsphub 1074
 
1.4%
1043
 
1.4%
azx6gtcda1 961
 
1.3%
azpv6cam200ion 894
 
1.2%
Other values (8837) 56782
74.8%
ValueCountFrequency (%)
azce6thinkrb 1964
 
10.0%
azce6bluefacecb 1532
 
7.8%
azce6bluezerocb 755
 
3.8%
azx6wsc5ger 666
 
3.4%
azce6flexa3 573
 
2.9%
azpv8cb1iaq 497
 
2.5%
azdi6bluefacecb 385
 
2.0%
azce6thinkcb 363
 
1.8%
azx6gtcda1 358
 
1.8%
azpv6ac1ant 338
 
1.7%
Other values (2013) 12306
62.3%
2024-12-29T11:10:20.604324image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 81634
 
10.1%
C 61020
 
7.6%
Z 56923
 
7.0%
E 52644
 
6.5%
6 45282
 
5.6%
B 39558
 
4.9%
0 35064
 
4.3%
T 34702
 
4.3%
I 32471
 
4.0%
R 32174
 
4.0%
Other values (92) 336130
41.6%
ValueCountFrequency (%)
A 26270
 
11.1%
C 22373
 
9.5%
Z 19186
 
8.1%
E 19083
 
8.1%
6 16791
 
7.1%
B 13842
 
5.9%
I 9780
 
4.1%
T 8505
 
3.6%
R 8175
 
3.5%
L 6371
 
2.7%
Other values (72) 85451
36.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 621036
76.9%
Decimal Number 136114
 
16.9%
Lowercase Letter 39069
 
4.8%
Space Separator 7792
 
1.0%
Other Punctuation 1876
 
0.2%
Dash Punctuation 1143
 
0.1%
Math Symbol 191
 
< 0.1%
Open Punctuation 131
 
< 0.1%
Connector Punctuation 91
 
< 0.1%
Close Punctuation 58
 
< 0.1%
Other values (5) 101
 
< 0.1%
ValueCountFrequency (%)
Uppercase Letter 193030
81.9%
Decimal Number 32069
 
13.6%
Lowercase Letter 9899
 
4.2%
Space Separator 476
 
0.2%
Other Punctuation 138
 
0.1%
Dash Punctuation 114
 
< 0.1%
Math Symbol 44
 
< 0.1%
Open Punctuation 22
 
< 0.1%
Connector Punctuation 13
 
< 0.1%
Control 10
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 81634
13.1%
C 61020
 
9.8%
Z 56923
 
9.2%
E 52644
 
8.5%
B 39558
 
6.4%
T 34702
 
5.6%
I 32471
 
5.2%
R 32174
 
5.2%
N 23452
 
3.8%
O 22545
 
3.6%
Other values (19) 183913
29.6%
ValueCountFrequency (%)
A 26270
13.6%
C 22373
11.6%
Z 19186
 
9.9%
E 19083
 
9.9%
B 13842
 
7.2%
I 9780
 
5.1%
T 8505
 
4.4%
R 8175
 
4.2%
L 6371
 
3.3%
N 6196
 
3.2%
Other values (16) 53249
27.6%
Decimal Number
ValueCountFrequency (%)
6 45282
33.3%
0 35064
25.8%
1 18297
13.4%
5 8806
 
6.5%
2 8130
 
6.0%
3 7302
 
5.4%
8 7037
 
5.2%
4 3619
 
2.7%
7 1625
 
1.2%
9 952
 
0.7%
ValueCountFrequency (%)
6 16791
52.4%
0 5198
 
16.2%
1 3646
 
11.4%
5 1627
 
5.1%
3 1591
 
5.0%
8 1545
 
4.8%
2 1114
 
3.5%
4 346
 
1.1%
7 195
 
0.6%
9 16
 
< 0.1%
Space Separator
ValueCountFrequency (%)
7788
99.9%
  4
 
0.1%
ValueCountFrequency (%)
476
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 4443
 
11.4%
e 4101
 
10.5%
c 3170
 
8.1%
z 2552
 
6.5%
t 2470
 
6.3%
r 2241
 
5.7%
i 2122
 
5.4%
n 1930
 
4.9%
b 1918
 
4.9%
o 1772
 
4.5%
Other values (25) 12350
31.6%
ValueCountFrequency (%)
a 1278
12.9%
c 1100
11.1%
e 1031
 
10.4%
z 923
 
9.3%
b 730
 
7.4%
i 538
 
5.4%
r 475
 
4.8%
t 454
 
4.6%
n 363
 
3.7%
p 354
 
3.6%
Other values (17) 2653
26.8%
Dash Punctuation
ValueCountFrequency (%)
- 1143
100.0%
ValueCountFrequency (%)
- 114
100.0%
Other Punctuation
ValueCountFrequency (%)
. 643
34.3%
* 559
29.8%
/ 328
17.5%
? 221
 
11.8%
: 85
 
4.5%
, 17
 
0.9%
\ 5
 
0.3%
' 5
 
0.3%
% 5
 
0.3%
; 4
 
0.2%
Other values (2) 4
 
0.2%
ValueCountFrequency (%)
? 58
42.0%
/ 38
27.5%
. 24
17.4%
, 6
 
4.3%
* 5
 
3.6%
% 4
 
2.9%
: 3
 
2.2%
Math Symbol
ValueCountFrequency (%)
+ 188
98.4%
> 2
 
1.0%
< 1
 
0.5%
ValueCountFrequency (%)
+ 43
97.7%
< 1
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 128
97.7%
[ 3
 
2.3%
ValueCountFrequency (%)
( 21
95.5%
[ 1
 
4.5%
Connector Punctuation
ValueCountFrequency (%)
_ 91
100.0%
ValueCountFrequency (%)
_ 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
96.6%
] 2
 
3.4%
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
° 55
100.0%
ValueCountFrequency (%)
° 2
100.0%
Control
ValueCountFrequency (%)
29
100.0%
ValueCountFrequency (%)
10
100.0%
Other Number
ValueCountFrequency (%)
² 3
100.0%
ValueCountFrequency (%)
² 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 2
100.0%
ValueCountFrequency (%)
¨ 1
100.0%
Other Letter
ValueCountFrequency (%)
º 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 660117
81.7%
Common 147485
 
18.3%
ValueCountFrequency (%)
Latin 202929
86.0%
Common 32898
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 81634
 
12.4%
C 61020
 
9.2%
Z 56923
 
8.6%
E 52644
 
8.0%
B 39558
 
6.0%
T 34702
 
5.3%
I 32471
 
4.9%
R 32174
 
4.9%
N 23452
 
3.6%
O 22545
 
3.4%
Other values (55) 222994
33.8%
ValueCountFrequency (%)
A 26270
12.9%
C 22373
 
11.0%
Z 19186
 
9.5%
E 19083
 
9.4%
B 13842
 
6.8%
I 9780
 
4.8%
T 8505
 
4.2%
R 8175
 
4.0%
L 6371
 
3.1%
N 6196
 
3.1%
Other values (43) 63148
31.1%
Common
ValueCountFrequency (%)
6 45282
30.7%
0 35064
23.8%
1 18297
12.4%
5 8806
 
6.0%
2 8130
 
5.5%
7788
 
5.3%
3 7302
 
5.0%
8 7037
 
4.8%
4 3619
 
2.5%
7 1625
 
1.1%
Other values (27) 4535
 
3.1%
ValueCountFrequency (%)
6 16791
51.0%
0 5198
 
15.8%
1 3646
 
11.1%
5 1627
 
4.9%
3 1591
 
4.8%
8 1545
 
4.7%
2 1114
 
3.4%
476
 
1.4%
4 346
 
1.1%
7 195
 
0.6%
Other values (19) 369
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 807406
> 99.9%
None 196
 
< 0.1%
ValueCountFrequency (%)
ASCII 235820
> 99.9%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 81634
 
10.1%
C 61020
 
7.6%
Z 56923
 
7.1%
E 52644
 
6.5%
6 45282
 
5.6%
B 39558
 
4.9%
0 35064
 
4.3%
T 34702
 
4.3%
I 32471
 
4.0%
R 32174
 
4.0%
Other values (75) 335934
41.6%
ValueCountFrequency (%)
A 26270
 
11.1%
C 22373
 
9.5%
Z 19186
 
8.1%
E 19083
 
8.1%
6 16791
 
7.1%
B 13842
 
5.9%
I 9780
 
4.1%
T 8505
 
3.6%
R 8175
 
3.5%
L 6371
 
2.7%
Other values (68) 85444
36.2%
None
ValueCountFrequency (%)
é 67
34.2%
° 55
28.1%
Ó 20
 
10.2%
ó 12
 
6.1%
º 12
 
6.1%
É 6
 
3.1%
è 5
 
2.6%
à 4
 
2.0%
  4
 
2.0%
² 3
 
1.5%
Other values (7) 8
 
4.1%
ValueCountFrequency (%)
é 2
28.6%
² 2
28.6%
° 2
28.6%
¨ 1
14.3%
Distinct17027
Distinct (%)33.5%
Missing19536
Missing (%)27.7%
Memory size4.8 MiB
2024-12-29T11:10:20.900715image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length50
Median length36
Mean length26.492817
Min length1

Characters and Unicode

Total characters1348140
Distinct characters135
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12053 ?
Unique (%)23.7%

Sample

1st rowTERMOSTATO BLUEFACE CABLE BLANCO
2nd rowTERMOSTATO LITE BLANCO CABLE
3rd rowTERMOSTATO LITE CABLE BLANCO
4th rowPASARELA SAMSUNG NO NASA
5th rowPASARELA SAMSUNG NO NASA
ValueCountFrequency (%)
airzone 11960
 
6.3%
termostato 7723
 
4.0%
de 6156
 
3.2%
thermostat 4095
 
2.1%
radio 3965
 
2.1%
think 3872
 
2.0%
blueface 3826
 
2.0%
cable 3352
 
1.8%
rejilla 3303
 
1.7%
central 2984
 
1.6%
Other values (6654) 139636
73.2%
2024-12-29T11:10:21.371940image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141253
 
10.5%
E 100112
 
7.4%
A 90538
 
6.7%
O 79087
 
5.9%
T 71460
 
5.3%
R 69630
 
5.2%
I 58468
 
4.3%
L 52745
 
3.9%
N 50480
 
3.7%
C 42720
 
3.2%
Other values (125) 591647
43.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 852504
63.2%
Lowercase Letter 275589
 
20.4%
Space Separator 141264
 
10.5%
Decimal Number 61558
 
4.6%
Other Punctuation 9046
 
0.7%
Dash Punctuation 4197
 
0.3%
Open Punctuation 1458
 
0.1%
Close Punctuation 1089
 
0.1%
Math Symbol 1031
 
0.1%
Other Letter 330
 
< 0.1%
Other values (7) 74
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38185
13.9%
a 26399
9.6%
o 25307
9.2%
r 23699
 
8.6%
i 20270
 
7.4%
t 20130
 
7.3%
n 19903
 
7.2%
l 17296
 
6.3%
c 12452
 
4.5%
m 11225
 
4.1%
Other values (34) 60723
22.0%
Uppercase Letter
ValueCountFrequency (%)
E 100112
11.7%
A 90538
10.6%
O 79087
 
9.3%
T 71460
 
8.4%
R 69630
 
8.2%
I 58468
 
6.9%
L 52745
 
6.2%
N 50480
 
5.9%
C 42720
 
5.0%
S 33873
 
4.0%
Other values (31) 203391
23.9%
Other Punctuation
ValueCountFrequency (%)
. 6272
69.3%
/ 1448
 
16.0%
* 533
 
5.9%
, 397
 
4.4%
\ 116
 
1.3%
' 86
 
1.0%
: 80
 
0.9%
? 51
 
0.6%
" 15
 
0.2%
& 12
 
0.1%
Other values (6) 36
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 21088
34.3%
2 7236
 
11.8%
1 7082
 
11.5%
6 6646
 
10.8%
3 6016
 
9.8%
5 5586
 
9.1%
8 4261
 
6.9%
4 2684
 
4.4%
7 657
 
1.1%
9 302
 
0.5%
Math Symbol
ValueCountFrequency (%)
+ 1013
98.3%
> 14
 
1.4%
< 3
 
0.3%
= 1
 
0.1%
Control
ValueCountFrequency (%)
8
66.7%
 2
 
16.7%
 2
 
16.7%
Space Separator
ValueCountFrequency (%)
141253
> 99.9%
  11
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 1448
99.3%
[ 10
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 1083
99.4%
] 6
 
0.6%
Other Letter
ValueCountFrequency (%)
º 327
99.1%
ª 3
 
0.9%
Currency Symbol
ValueCountFrequency (%)
2
66.7%
$ 1
33.3%
Modifier Symbol
ValueCountFrequency (%)
´ 1
50.0%
` 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 4197
100.0%
Other Symbol
ValueCountFrequency (%)
° 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1128421
83.7%
Common 219719
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 100112
 
8.9%
A 90538
 
8.0%
O 79087
 
7.0%
T 71460
 
6.3%
R 69630
 
6.2%
I 58468
 
5.2%
L 52745
 
4.7%
N 50480
 
4.5%
C 42720
 
3.8%
e 38185
 
3.4%
Other values (76) 474996
42.1%
Common
ValueCountFrequency (%)
141253
64.3%
0 21088
 
9.6%
2 7236
 
3.3%
1 7082
 
3.2%
6 6646
 
3.0%
. 6272
 
2.9%
3 6016
 
2.7%
5 5586
 
2.5%
8 4261
 
1.9%
- 4197
 
1.9%
Other values (39) 10082
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1345511
99.8%
None 2625
 
0.2%
Punctuation 2
 
< 0.1%
Currency Symbols 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141253
 
10.5%
E 100112
 
7.4%
A 90538
 
6.7%
O 79087
 
5.9%
T 71460
 
5.3%
R 69630
 
5.2%
I 58468
 
4.3%
L 52745
 
3.9%
N 50480
 
3.8%
C 42720
 
3.2%
Other values (80) 589018
43.8%
None
ValueCountFrequency (%)
é 818
31.2%
Ó 419
16.0%
ó 341
13.0%
º 327
 
12.5%
Á 133
 
5.1%
è 97
 
3.7%
á 68
 
2.6%
â 63
 
2.4%
É 53
 
2.0%
Ø 44
 
1.7%
Other values (33) 262
 
10.0%
Punctuation
ValueCountFrequency (%)
2
100.0%
Currency Symbols
ValueCountFrequency (%)
2
100.0%
Distinct35095
Distinct (%)50.9%
Missing1508
Missing (%)2.1%
Memory size4.2 MiB
2024-12-29T11:10:21.658305image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.3455561
Min length1

Characters and Unicode

Total characters437304
Distinct characters101
Distinct categories16 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32409 ?
Unique (%)47.0%

Sample

1st rowNO DISPONI
2nd rowNO DISPONI
3rd rowF00K2QH
4th row00HJNZ
5th row00LSS7
ValueCountFrequency (%)
9505
 
12.5%
no 2754
 
3.6%
xxxx 1583
 
2.1%
8435418928 1045
 
1.4%
0000 1032
 
1.4%
dispong 1016
 
1.3%
xxx 961
 
1.3%
ticket 901
 
1.2%
nc 816
 
1.1%
000000 766
 
1.0%
Other values (34539) 55559
73.2%
2024-12-29T11:10:22.083295image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89916
20.6%
1 19930
 
4.6%
X 18336
 
4.2%
4 17323
 
4.0%
F 16442
 
3.8%
8 15057
 
3.4%
5 14752
 
3.4%
N 13072
 
3.0%
3 12523
 
2.9%
9 10676
 
2.4%
Other values (91) 209277
47.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203892
46.6%
Uppercase Letter 182979
41.8%
Lowercase Letter 24403
 
5.6%
Other Punctuation 11049
 
2.5%
Space Separator 7521
 
1.7%
Dash Punctuation 6939
 
1.6%
Other Symbol 263
 
0.1%
Math Symbol 139
 
< 0.1%
Connector Punctuation 35
 
< 0.1%
Other Letter 31
 
< 0.1%
Other values (6) 53
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
x 5236
21.5%
n 2520
 
10.3%
o 1889
 
7.7%
i 1391
 
5.7%
e 1338
 
5.5%
s 1210
 
5.0%
c 1167
 
4.8%
t 1016
 
4.2%
d 963
 
3.9%
a 926
 
3.8%
Other values (24) 6747
27.6%
Uppercase Letter
ValueCountFrequency (%)
X 18336
 
10.0%
F 16442
 
9.0%
N 13072
 
7.1%
C 10494
 
5.7%
A 10423
 
5.7%
D 8588
 
4.7%
I 8008
 
4.4%
E 7777
 
4.3%
O 7255
 
4.0%
S 7136
 
3.9%
Other values (20) 75448
41.2%
Other Punctuation
ValueCountFrequency (%)
* 5234
47.4%
. 2466
22.3%
/ 1862
 
16.9%
? 802
 
7.3%
: 439
 
4.0%
, 124
 
1.1%
; 45
 
0.4%
\ 24
 
0.2%
' 20
 
0.2%
¿ 14
 
0.1%
Other values (4) 19
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 89916
44.1%
1 19930
 
9.8%
4 17323
 
8.5%
8 15057
 
7.4%
5 14752
 
7.2%
3 12523
 
6.1%
9 10676
 
5.2%
2 10319
 
5.1%
6 7133
 
3.5%
7 6263
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 23
95.8%
[ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
7521
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6939
100.0%
Other Symbol
ValueCountFrequency (%)
° 263
100.0%
Math Symbol
ValueCountFrequency (%)
+ 139
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 35
100.0%
Other Letter
ValueCountFrequency (%)
º 31
100.0%
Control
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 7
100.0%
Other Number
ValueCountFrequency (%)
² 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 229899
52.6%
Latin 207405
47.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
X 18336
 
8.8%
F 16442
 
7.9%
N 13072
 
6.3%
C 10494
 
5.1%
A 10423
 
5.0%
D 8588
 
4.1%
I 8008
 
3.9%
E 7777
 
3.7%
O 7255
 
3.5%
S 7136
 
3.4%
Other values (54) 99874
48.2%
Common
ValueCountFrequency (%)
0 89916
39.1%
1 19930
 
8.7%
4 17323
 
7.5%
8 15057
 
6.5%
5 14752
 
6.4%
3 12523
 
5.4%
9 10676
 
4.6%
2 10319
 
4.5%
7521
 
3.3%
6 7133
 
3.1%
Other values (27) 24749
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 436839
99.9%
None 465
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89916
20.6%
1 19930
 
4.6%
X 18336
 
4.2%
4 17323
 
4.0%
F 16442
 
3.8%
8 15057
 
3.4%
5 14752
 
3.4%
N 13072
 
3.0%
3 12523
 
2.9%
9 10676
 
2.4%
Other values (73) 208812
47.8%
None
ValueCountFrequency (%)
° 263
56.6%
é 61
 
13.1%
à 45
 
9.7%
º 31
 
6.7%
¿ 14
 
3.0%
Ø 12
 
2.6%
ó 8
 
1.7%
µ 8
 
1.7%
Ó 6
 
1.3%
É 4
 
0.9%
Other values (8) 13
 
2.8%
Distinct19710
Distinct (%)48.9%
Missing30101
Missing (%)42.7%
Memory size3.6 MiB
2024-12-29T11:10:22.295644image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length60
Median length58
Mean length10.80254
Min length1

Characters and Unicode

Total characters435580
Distinct characters108
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14677 ?
Unique (%)36.4%

Sample

1st row1/11912209
2nd row1/11912209
3rd row1/11916095
4th row21805007
5th row21405974
ValueCountFrequency (%)
3452
 
5.9%
no 1814
 
3.1%
dispongo 819
 
1.4%
00000 660
 
1.1%
xxxx 602
 
1.0%
albaran 518
 
0.9%
pedido 504
 
0.9%
del 485
 
0.8%
factura 468
 
0.8%
xxx 430
 
0.7%
Other values (22059) 48483
83.3%
2024-12-29T11:10:22.694664image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 64037
14.7%
0 53294
 
12.2%
1 47457
 
10.9%
3 23376
 
5.4%
4 20677
 
4.7%
18610
 
4.3%
6 17280
 
4.0%
5 14773
 
3.4%
7 14725
 
3.4%
8 13949
 
3.2%
Other values (98) 147402
33.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283201
65.0%
Uppercase Letter 86790
 
19.9%
Lowercase Letter 21473
 
4.9%
Other Punctuation 18889
 
4.3%
Space Separator 18610
 
4.3%
Dash Punctuation 5466
 
1.3%
Other Letter 346
 
0.1%
Other Symbol 229
 
0.1%
Connector Punctuation 219
 
0.1%
Open Punctuation 129
 
< 0.1%
Other values (5) 228
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2314
10.8%
a 2099
 
9.8%
o 1767
 
8.2%
n 1758
 
8.2%
d 1564
 
7.3%
i 1497
 
7.0%
r 1301
 
6.1%
c 1197
 
5.6%
t 1162
 
5.4%
l 1044
 
4.9%
Other values (27) 5770
26.9%
Uppercase Letter
ValueCountFrequency (%)
A 11125
12.8%
O 7571
 
8.7%
N 6931
 
8.0%
S 6386
 
7.4%
E 5583
 
6.4%
I 5554
 
6.4%
R 5257
 
6.1%
X 5136
 
5.9%
D 4606
 
5.3%
P 3812
 
4.4%
Other values (22) 24829
28.6%
Other Punctuation
ValueCountFrequency (%)
/ 13685
72.4%
* 2606
 
13.8%
. 1700
 
9.0%
: 406
 
2.1%
, 377
 
2.0%
? 34
 
0.2%
\ 26
 
0.1%
' 26
 
0.1%
; 19
 
0.1%
# 4
 
< 0.1%
Other values (4) 6
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 64037
22.6%
0 53294
18.8%
1 47457
16.8%
3 23376
 
8.3%
4 20677
 
7.3%
6 17280
 
6.1%
5 14773
 
5.2%
7 14725
 
5.2%
8 13949
 
4.9%
9 13633
 
4.8%
Math Symbol
ValueCountFrequency (%)
+ 86
91.5%
| 6
 
6.4%
> 1
 
1.1%
< 1
 
1.1%
Other Letter
ValueCountFrequency (%)
º 340
98.3%
ª 6
 
1.7%
Space Separator
ValueCountFrequency (%)
18610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5466
100.0%
Other Symbol
ValueCountFrequency (%)
° 229
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 326971
75.1%
Latin 108609
 
24.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 11125
 
10.2%
O 7571
 
7.0%
N 6931
 
6.4%
S 6386
 
5.9%
E 5583
 
5.1%
I 5554
 
5.1%
R 5257
 
4.8%
X 5136
 
4.7%
D 4606
 
4.2%
P 3812
 
3.5%
Other values (61) 46648
43.0%
Common
ValueCountFrequency (%)
2 64037
19.6%
0 53294
16.3%
1 47457
14.5%
3 23376
 
7.1%
4 20677
 
6.3%
18610
 
5.7%
6 17280
 
5.3%
5 14773
 
4.5%
7 14725
 
4.5%
8 13949
 
4.3%
Other values (27) 38793
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434646
99.8%
None 934
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 64037
14.7%
0 53294
 
12.3%
1 47457
 
10.9%
3 23376
 
5.4%
4 20677
 
4.8%
18610
 
4.3%
6 17280
 
4.0%
5 14773
 
3.4%
7 14725
 
3.4%
8 13949
 
3.2%
Other values (75) 146468
33.7%
None
ValueCountFrequency (%)
º 340
36.4%
° 229
24.5%
Á 114
 
12.2%
á 109
 
11.7%
é 46
 
4.9%
Ó 25
 
2.7%
Ñ 19
 
2.0%
ó 12
 
1.3%
É 7
 
0.7%
ª 6
 
0.6%
Other values (13) 27
 
2.9%
Distinct39897
Distinct (%)57.8%
Missing1427
Missing (%)2.0%
Memory size8.2 MiB
2024-12-29T11:10:22.991967image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length250
Median length228
Mean length42.525523
Min length1

Characters and Unicode

Total characters2934091
Distinct characters149
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33858 ?
Unique (%)49.1%

Sample

1st rowNECESITAMOS CAMBIO A TERMOSTATO THINK RADIO BLANCO.
2nd rowNECESITAMOS CAMBIO A TERMOSTATO LITE RADIO BLANCO, 3 UDS.
3rd rowNECCESITAMOS QUE NOS ENVIEN 1 TERMOSTATO RADIO AZRA6LITERB
4th rowSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM2
5th rowSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM2
ValueCountFrequency (%)
de 16394
 
3.5%
no 9746
 
2.1%
la 9683
 
2.1%
el 7908
 
1.7%
en 7727
 
1.7%
se 6262
 
1.4%
5877
 
1.3%
por 5844
 
1.3%
que 4928
 
1.1%
y 4887
 
1.1%
Other values (33774) 383013
82.9%
2024-12-29T11:10:23.467007image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
388450
 
13.2%
E 162137
 
5.5%
e 135280
 
4.6%
A 135091
 
4.6%
O 117742
 
4.0%
N 109000
 
3.7%
a 99115
 
3.4%
I 92971
 
3.2%
R 91947
 
3.1%
o 87322
 
3.0%
Other values (139) 1515036
51.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1293797
44.1%
Lowercase Letter 1001220
34.1%
Space Separator 388457
 
13.2%
Decimal Number 169126
 
5.8%
Other Punctuation 42653
 
1.5%
Control 23298
 
0.8%
Dash Punctuation 4886
 
0.2%
Other Symbol 3609
 
0.1%
Open Punctuation 2200
 
0.1%
Close Punctuation 2128
 
0.1%
Other values (7) 2717
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 135280
13.5%
a 99115
9.9%
o 87322
 
8.7%
n 78178
 
7.8%
i 72603
 
7.3%
r 68738
 
6.9%
t 66081
 
6.6%
l 57221
 
5.7%
s 55246
 
5.5%
c 47863
 
4.8%
Other values (38) 233573
23.3%
Uppercase Letter
ValueCountFrequency (%)
E 162137
12.5%
A 135091
10.4%
O 117742
 
9.1%
N 109000
 
8.4%
I 92971
 
7.2%
R 91947
 
7.1%
T 81223
 
6.3%
S 67697
 
5.2%
L 67211
 
5.2%
C 63555
 
4.9%
Other values (36) 305223
23.6%
Other Punctuation
ValueCountFrequency (%)
. 18429
43.2%
, 10663
25.0%
\ 3445
 
8.1%
' 3056
 
7.2%
: 2533
 
5.9%
/ 2315
 
5.4%
? 716
 
1.7%
* 707
 
1.7%
" 284
 
0.7%
! 217
 
0.5%
Other values (8) 288
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 33415
19.8%
2 28976
17.1%
1 24915
14.7%
3 15340
9.1%
4 14685
8.7%
6 13760
8.1%
5 11407
 
6.7%
8 9160
 
5.4%
7 8951
 
5.3%
9 8517
 
5.0%
Math Symbol
ValueCountFrequency (%)
+ 776
81.5%
> 96
 
10.1%
= 59
 
6.2%
< 21
 
2.2%
Modifier Symbol
ValueCountFrequency (%)
´ 5
45.5%
` 4
36.4%
¨ 1
 
9.1%
^ 1
 
9.1%
Control
ValueCountFrequency (%)
11500
49.4%
11497
49.3%
301
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 2196
99.8%
[ 3
 
0.1%
{ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2124
99.8%
] 3
 
0.1%
} 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
388450
> 99.9%
  7
 
< 0.1%
Other Letter
ValueCountFrequency (%)
º 929
91.2%
ª 90
 
8.8%
Dash Punctuation
ValueCountFrequency (%)
- 4886
100.0%
Other Symbol
ValueCountFrequency (%)
° 3609
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 709
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 13
100.0%
Final Punctuation
ValueCountFrequency (%)
» 12
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2296035
78.3%
Common 638056
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 162137
 
7.1%
e 135280
 
5.9%
A 135091
 
5.9%
O 117742
 
5.1%
N 109000
 
4.7%
a 99115
 
4.3%
I 92971
 
4.0%
R 91947
 
4.0%
o 87322
 
3.8%
T 81223
 
3.5%
Other values (85) 1184207
51.6%
Common
ValueCountFrequency (%)
388450
60.9%
0 33415
 
5.2%
2 28976
 
4.5%
1 24915
 
3.9%
. 18429
 
2.9%
3 15340
 
2.4%
4 14685
 
2.3%
6 13760
 
2.2%
11500
 
1.8%
11497
 
1.8%
Other values (44) 77089
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2905326
99.0%
None 28765
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
388450
 
13.4%
E 162137
 
5.6%
e 135280
 
4.7%
A 135091
 
4.6%
O 117742
 
4.1%
N 109000
 
3.8%
a 99115
 
3.4%
I 92971
 
3.2%
R 91947
 
3.2%
o 87322
 
3.0%
Other values (85) 1486271
51.2%
None
ValueCountFrequency (%)
é 9112
31.7%
ó 3760
13.1%
° 3609
 
12.5%
Ó 2436
 
8.5%
è 1826
 
6.3%
í 1399
 
4.9%
á 969
 
3.4%
à 967
 
3.4%
º 929
 
3.2%
Í 595
 
2.1%
Other values (44) 3163
 
11.0%
Distinct2
Distinct (%)< 0.1%
Missing1426
Missing (%)2.0%
Memory size3.9 MiB
2024-12-29T11:10:23.557051image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters68997
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 68822
99.7%
1 175
 
0.3%
2024-12-29T11:10:23.771008image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68822
99.7%
1 175
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68997
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 68822
99.7%
1 175
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 68997
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 68822
99.7%
1 175
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 68822
99.7%
1 175
 
0.3%
Distinct68910
Distinct (%)99.9%
Missing1426
Missing (%)2.0%
Memory size550.3 KiB
Minimum2020-01-02 09:03:18
Maximum2024-09-30 18:09:25
Invalid dates0
Invalid dates (%)0.0%
2024-12-29T11:10:23.908897image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2024-12-29T11:10:24.077787image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct68905
Distinct (%)99.9%
Missing1426
Missing (%)2.0%
Memory size550.3 KiB
Minimum2020-01-02 09:03:18
Maximum2024-10-07 14:46:55
Invalid dates0
Invalid dates (%)0.0%
2024-12-29T11:10:24.246889image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
2024-12-29T11:10:24.413474image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

id_estado
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.733908
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:24.546954image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q16
median6
Q36
95-th percentile76
Maximum76
Range75
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.79176
Coefficient of variation (CV)1.6327871
Kurtosis5.3647795
Mean12.733908
Median Absolute Deviation (MAD)0
Skewness2.7128909
Sum896760
Variance432.2973
MonotonicityNot monotonic
2024-12-29T11:10:24.672788image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 60356
85.7%
76 6862
 
9.7%
4 2589
 
3.7%
5 526
 
0.7%
1 54
 
0.1%
2 36
 
0.1%
ValueCountFrequency (%)
1 54
 
0.1%
2 36
 
0.1%
4 2589
 
3.7%
5 526
 
0.7%
6 60356
85.7%
76 6862
 
9.7%
ValueCountFrequency (%)
76 6862
 
9.7%
6 60356
85.7%
5 526
 
0.7%
4 2589
 
3.7%
2 36
 
0.1%
1 54
 
0.1%

ref
Text

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2024-12-29T11:10:24.805680image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters774653
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGARANTIA-ES
2nd rowGARANTIA-ES
3rd rowGARANTIA-ES
4th rowGARANTIA-ES
5th rowGARANTIA-ES
ValueCountFrequency (%)
garantia-es 70423
100.0%
2024-12-29T11:10:25.066483image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 211269
27.3%
G 70423
 
9.1%
R 70423
 
9.1%
N 70423
 
9.1%
T 70423
 
9.1%
I 70423
 
9.1%
- 70423
 
9.1%
E 70423
 
9.1%
S 70423
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 704230
90.9%
Dash Punctuation 70423
 
9.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 211269
30.0%
G 70423
 
10.0%
R 70423
 
10.0%
N 70423
 
10.0%
T 70423
 
10.0%
I 70423
 
10.0%
E 70423
 
10.0%
S 70423
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 70423
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 704230
90.9%
Common 70423
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 211269
30.0%
G 70423
 
10.0%
R 70423
 
10.0%
N 70423
 
10.0%
T 70423
 
10.0%
I 70423
 
10.0%
E 70423
 
10.0%
S 70423
 
10.0%
Common
ValueCountFrequency (%)
- 70423
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 774653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 211269
27.3%
G 70423
 
9.1%
R 70423
 
9.1%
N 70423
 
9.1%
T 70423
 
9.1%
I 70423
 
9.1%
- 70423
 
9.1%
E 70423
 
9.1%
S 70423
 
9.1%

color
Text

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.2 MiB
2024-12-29T11:10:25.186798image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters422538
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF7A54A
2nd rowF7A54A
3rd row18A689
4th row18A689
5th row18A689
ValueCountFrequency (%)
18a689 60356
85.7%
cc0000 6862
 
9.7%
1a7bb9 2625
 
3.7%
f7a54a 526
 
0.7%
ec4758 54
 
0.1%
2024-12-29T11:10:25.445362image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 120766
28.6%
A 64033
15.2%
1 62981
14.9%
9 62981
14.9%
6 60356
14.3%
0 27448
 
6.5%
C 13778
 
3.3%
B 5250
 
1.2%
7 3205
 
0.8%
5 580
 
0.1%
Other values (3) 1160
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 338897
80.2%
Uppercase Letter 83641
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 120766
35.6%
1 62981
18.6%
9 62981
18.6%
6 60356
17.8%
0 27448
 
8.1%
7 3205
 
0.9%
5 580
 
0.2%
4 580
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
A 64033
76.6%
C 13778
 
16.5%
B 5250
 
6.3%
F 526
 
0.6%
E 54
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 338897
80.2%
Latin 83641
 
19.8%

Most frequent character per script

Common
ValueCountFrequency (%)
8 120766
35.6%
1 62981
18.6%
9 62981
18.6%
6 60356
17.8%
0 27448
 
8.1%
7 3205
 
0.9%
5 580
 
0.2%
4 580
 
0.2%
Latin
ValueCountFrequency (%)
A 64033
76.6%
C 13778
 
16.5%
B 5250
 
6.3%
F 526
 
0.6%
E 54
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422538
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 120766
28.6%
A 64033
15.2%
1 62981
14.9%
9 62981
14.9%
6 60356
14.3%
0 27448
 
6.5%
C 13778
 
3.3%
B 5250
 
1.2%
7 3205
 
0.8%
5 580
 
0.1%
Other values (3) 1160
 
0.3%

valor
Text

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.0 MiB
2024-12-29T11:10:25.539378image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9544893
Min length2

Characters and Unicode

Total characters208064
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row80
2nd row80
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 67218
95.4%
60 2589
 
3.7%
80 526
 
0.7%
12 54
 
0.1%
26 36
 
0.1%
2024-12-29T11:10:25.778827image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137551
66.1%
1 67272
32.3%
6 2625
 
1.3%
8 526
 
0.3%
2 90
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208064
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137551
66.1%
1 67272
32.3%
6 2625
 
1.3%
8 526
 
0.3%
2 90
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 208064
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 137551
66.1%
1 67272
32.3%
6 2625
 
1.3%
8 526
 
0.3%
2 90
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137551
66.1%
1 67272
32.3%
6 2625
 
1.3%
8 526
 
0.3%
2 90
 
< 0.1%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
2024-12-29T11:10:25.916380image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length11
Median length7
Mean length7.1699729
Min length7

Characters and Unicode

Total characters504931
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR.Validada
2nd rowR.Validada
3rd rowCerrada
4th rowCerrada
5th rowCerrada
ValueCountFrequency (%)
cerrada 60356
85.7%
anulada 6862
 
9.7%
r.tramitada 2589
 
3.7%
r.validada 526
 
0.7%
abierta 54
 
0.1%
validada 36
 
0.1%
2024-12-29T11:10:26.219317image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 143943
28.5%
r 123355
24.4%
d 70931
14.0%
e 60410
12.0%
C 60356
12.0%
l 7424
 
1.5%
A 6916
 
1.4%
n 6862
 
1.4%
u 6862
 
1.4%
i 3205
 
0.6%
Other values (7) 14667
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 428278
84.8%
Uppercase Letter 73538
 
14.6%
Other Punctuation 3115
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 143943
33.6%
r 123355
28.8%
d 70931
16.6%
e 60410
14.1%
l 7424
 
1.7%
n 6862
 
1.6%
u 6862
 
1.6%
i 3205
 
0.7%
t 2643
 
0.6%
m 2589
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 60356
82.1%
A 6916
 
9.4%
R 3115
 
4.2%
T 2589
 
3.5%
V 562
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 3115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 501816
99.4%
Common 3115
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 143943
28.7%
r 123355
24.6%
d 70931
14.1%
e 60410
12.0%
C 60356
12.0%
l 7424
 
1.5%
A 6916
 
1.4%
n 6862
 
1.4%
u 6862
 
1.4%
i 3205
 
0.6%
Other values (6) 11552
 
2.3%
Common
ValueCountFrequency (%)
. 3115
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 143943
28.5%
r 123355
24.4%
d 70931
14.0%
e 60410
12.0%
C 60356
12.0%
l 7424
 
1.5%
A 6916
 
1.4%
n 6862
 
1.4%
u 6862
 
1.4%
i 3205
 
0.6%
Other values (7) 14667
 
2.9%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
2024-12-29T11:10:26.345884image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length15
Median length6
Mean length6.5428482
Min length4

Characters and Unicode

Total characters460767
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccepted pickup
2nd rowAccepted pickup
3rd rowClosed
4th rowClosed
5th rowClosed
ValueCountFrequency (%)
closed 60356
85.1%
anuladaen 6862
 
9.7%
r.tramitada 2589
 
3.6%
accepted 562
 
0.8%
pickup 526
 
0.7%
open 54
 
0.1%
2024-12-29T11:10:26.612417image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 70369
15.3%
l 67218
14.6%
e 61534
13.4%
C 60356
13.1%
o 60356
13.1%
s 60356
13.1%
a 21491
 
4.7%
A 7424
 
1.6%
u 7388
 
1.6%
n 6916
 
1.5%
Other values (14) 37359
8.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 370916
80.5%
Uppercase Letter 86736
 
18.8%
Other Punctuation 2589
 
0.6%
Space Separator 526
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 70369
19.0%
l 67218
18.1%
e 61534
16.6%
o 60356
16.3%
s 60356
16.3%
a 21491
 
5.8%
u 7388
 
2.0%
n 6916
 
1.9%
t 3151
 
0.8%
i 3115
 
0.8%
Other values (5) 9022
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
C 60356
69.6%
A 7424
 
8.6%
E 6862
 
7.9%
N 6862
 
7.9%
R 2589
 
3.0%
T 2589
 
3.0%
O 54
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 2589
100.0%
Space Separator
ValueCountFrequency (%)
526
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 457652
99.3%
Common 3115
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 70369
15.4%
l 67218
14.7%
e 61534
13.4%
C 60356
13.2%
o 60356
13.2%
s 60356
13.2%
a 21491
 
4.7%
A 7424
 
1.6%
u 7388
 
1.6%
n 6916
 
1.5%
Other values (12) 34244
7.5%
Common
ValueCountFrequency (%)
. 2589
83.1%
526
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 460767
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 70369
15.3%
l 67218
14.6%
e 61534
13.4%
C 60356
13.1%
o 60356
13.1%
s 60356
13.1%
a 21491
 
4.7%
A 7424
 
1.6%
u 7388
 
1.6%
n 6916
 
1.5%
Other values (14) 37359
8.1%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.3 MiB
2024-12-29T11:10:26.743806image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length15
Median length6
Mean length6.4898542
Min length6

Characters and Unicode

Total characters457035
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRetour accepté
2nd rowRetour accepté
3rd rowFermée
4th rowFermée
5th rowFermée
ValueCountFrequency (%)
fermée 60356
79.3%
annulée 6862
 
9.0%
retour 3115
 
4.1%
en 2589
 
3.4%
cours 2589
 
3.4%
accepté 526
 
0.7%
ouverte 54
 
0.1%
acceptée 36
 
< 0.1%
2024-12-29T11:10:27.005379image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 133984
29.3%
é 67780
14.8%
r 66114
14.5%
F 60356
13.2%
m 60356
13.2%
n 16313
 
3.6%
u 12620
 
2.8%
A 6898
 
1.5%
l 6862
 
1.5%
o 5704
 
1.2%
Other values (9) 20048
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 380908
83.3%
Uppercase Letter 70423
 
15.4%
Space Separator 5704
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 133984
35.2%
é 67780
17.8%
r 66114
17.4%
m 60356
15.8%
n 16313
 
4.3%
u 12620
 
3.3%
l 6862
 
1.8%
o 5704
 
1.5%
t 3731
 
1.0%
c 3713
 
1.0%
Other values (4) 3731
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
F 60356
85.7%
A 6898
 
9.8%
R 3115
 
4.4%
O 54
 
0.1%
Space Separator
ValueCountFrequency (%)
5704
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 451331
98.8%
Common 5704
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 133984
29.7%
é 67780
15.0%
r 66114
14.6%
F 60356
13.4%
m 60356
13.4%
n 16313
 
3.6%
u 12620
 
2.8%
A 6898
 
1.5%
l 6862
 
1.5%
o 5704
 
1.3%
Other values (8) 14344
 
3.2%
Common
ValueCountFrequency (%)
5704
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 389255
85.2%
None 67780
 
14.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 133984
34.4%
r 66114
17.0%
F 60356
15.5%
m 60356
15.5%
n 16313
 
4.2%
u 12620
 
3.2%
A 6898
 
1.8%
l 6862
 
1.8%
o 5704
 
1.5%
5704
 
1.5%
Other values (8) 14344
 
3.7%
None
ValueCountFrequency (%)
é 67780
100.0%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.3 MiB
2024-12-29T11:10:27.130786image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length15
Median length6
Mean length6.6770089
Min length6

Characters and Unicode

Total characters470215
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVerifica reso
2nd rowVerifica reso
3rd rowChiusa
4th rowChiusa
5th rowChiusa
ValueCountFrequency (%)
chiusa 60356
79.3%
annullata 6862
 
9.0%
ritiro 2589
 
3.4%
in 2589
 
3.4%
corso 2589
 
3.4%
verifica 526
 
0.7%
reso 526
 
0.7%
aperta 54
 
0.1%
accettata 36
 
< 0.1%
2024-12-29T11:10:27.381420image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 74732
15.9%
i 69175
14.7%
u 67218
14.3%
s 63471
13.5%
C 60356
12.8%
h 60356
12.8%
n 16313
 
3.5%
l 13724
 
2.9%
t 9613
 
2.0%
o 8293
 
1.8%
Other values (9) 26964
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 394088
83.8%
Uppercase Letter 70423
 
15.0%
Space Separator 5704
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 74732
19.0%
i 69175
17.6%
u 67218
17.1%
s 63471
16.1%
h 60356
15.3%
n 16313
 
4.1%
l 13724
 
3.5%
t 9613
 
2.4%
o 8293
 
2.1%
r 6284
 
1.6%
Other values (4) 4909
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
C 60356
85.7%
A 6952
 
9.9%
R 2589
 
3.7%
V 526
 
0.7%
Space Separator
ValueCountFrequency (%)
5704
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 464511
98.8%
Common 5704
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 74732
16.1%
i 69175
14.9%
u 67218
14.5%
s 63471
13.7%
C 60356
13.0%
h 60356
13.0%
n 16313
 
3.5%
l 13724
 
3.0%
t 9613
 
2.1%
o 8293
 
1.8%
Other values (8) 21260
 
4.6%
Common
ValueCountFrequency (%)
5704
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 470215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 74732
15.9%
i 69175
14.7%
u 67218
14.3%
s 63471
13.5%
C 60356
12.8%
h 60356
12.8%
n 16313
 
3.5%
l 13724
 
2.9%
t 9613
 
2.0%
o 8293
 
1.8%
Other values (9) 26964
 
5.7%

titulo_pt
Unsupported

Missing70423
Missing (%)100.0%
Memory size550.3 KiB

id_tipo
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.4434031
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size619.1 KiB
2024-12-29T11:10:27.495227image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2
Maximum3
Range2
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.53161546
Coefficient of variation (CV)0.36830701
Kurtosis-0.91586016
Mean1.4434031
Median Absolute Deviation (MAD)0
Skewness0.58400148
Sum101643
Variance0.282615
MonotonicityNot monotonic
2024-12-29T11:10:27.621979image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
1 40456
57.4%
2 28702
40.8%
3 1261
 
1.8%
(Missing) 4
 
< 0.1%
ValueCountFrequency (%)
1 40456
57.4%
2 28702
40.8%
3 1261
 
1.8%
ValueCountFrequency (%)
3 1261
 
1.8%
2 28702
40.8%
1 40456
57.4%
Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size4.4 MiB
2024-12-29T11:10:27.755372image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.8509919
Min length8

Characters and Unicode

Total characters623278
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdevolucion
2nd rowdevolucion
3rd rowdevolucion
4th rowdevolucion
5th rowdevolucion
ValueCountFrequency (%)
garantia 40456
57.5%
devolucion 28702
40.8%
reparacion 1261
 
1.8%
2024-12-29T11:10:28.036147image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 123890
19.9%
n 70419
11.3%
i 70419
11.3%
o 58665
9.4%
r 42978
 
6.9%
g 40456
 
6.5%
t 40456
 
6.5%
e 29963
 
4.8%
c 29963
 
4.8%
d 28702
 
4.6%
Other values (4) 87367
14.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 623278
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 123890
19.9%
n 70419
11.3%
i 70419
11.3%
o 58665
9.4%
r 42978
 
6.9%
g 40456
 
6.5%
t 40456
 
6.5%
e 29963
 
4.8%
c 29963
 
4.8%
d 28702
 
4.6%
Other values (4) 87367
14.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 623278
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 123890
19.9%
n 70419
11.3%
i 70419
11.3%
o 58665
9.4%
r 42978
 
6.9%
g 40456
 
6.5%
t 40456
 
6.5%
e 29963
 
4.8%
c 29963
 
4.8%
d 28702
 
4.6%
Other values (4) 87367
14.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 623278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 123890
19.9%
n 70419
11.3%
i 70419
11.3%
o 58665
9.4%
r 42978
 
6.9%
g 40456
 
6.5%
t 40456
 
6.5%
e 29963
 
4.8%
c 29963
 
4.8%
d 28702
 
4.6%
Other values (4) 87367
14.0%
Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size4.3 MiB
2024-12-29T11:10:28.166507image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length7.7235121
Min length6

Characters and Unicode

Total characters543882
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowreturn
2nd rowreturn
3rd rowreturn
4th rowreturn
5th rowreturn
ValueCountFrequency (%)
guarantee 40456
57.5%
return 28702
40.8%
repair 1261
 
1.8%
2024-12-29T11:10:28.432343image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 110875
20.4%
r 100382
18.5%
a 82173
15.1%
u 69158
12.7%
n 69158
12.7%
t 69158
12.7%
g 40456
 
7.4%
p 1261
 
0.2%
i 1261
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 543882
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 110875
20.4%
r 100382
18.5%
a 82173
15.1%
u 69158
12.7%
n 69158
12.7%
t 69158
12.7%
g 40456
 
7.4%
p 1261
 
0.2%
i 1261
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 543882
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 110875
20.4%
r 100382
18.5%
a 82173
15.1%
u 69158
12.7%
n 69158
12.7%
t 69158
12.7%
g 40456
 
7.4%
p 1261
 
0.2%
i 1261
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 543882
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 110875
20.4%
r 100382
18.5%
a 82173
15.1%
u 69158
12.7%
n 69158
12.7%
t 69158
12.7%
g 40456
 
7.4%
p 1261
 
0.2%
i 1261
 
0.2%
Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size4.3 MiB
2024-12-29T11:10:28.562993image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.2206365
Min length6

Characters and Unicode

Total characters508470
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowretour
2nd rowretour
3rd rowretour
4th rowretour
5th rowretour
ValueCountFrequency (%)
garantie 40456
57.5%
retour 28702
40.8%
reparation 1261
 
1.8%
2024-12-29T11:10:28.845022image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 100382
19.7%
a 83434
16.4%
t 70419
13.8%
e 70419
13.8%
n 41717
8.2%
i 41717
8.2%
g 40456
8.0%
o 29963
 
5.9%
u 28702
 
5.6%
p 1261
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 508470
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 100382
19.7%
a 83434
16.4%
t 70419
13.8%
e 70419
13.8%
n 41717
8.2%
i 41717
8.2%
g 40456
8.0%
o 29963
 
5.9%
u 28702
 
5.6%
p 1261
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 508470
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 100382
19.7%
a 83434
16.4%
t 70419
13.8%
e 70419
13.8%
n 41717
8.2%
i 41717
8.2%
g 40456
8.0%
o 29963
 
5.9%
u 28702
 
5.6%
p 1261
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 508470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 100382
19.7%
a 83434
16.4%
t 70419
13.8%
e 70419
13.8%
n 41717
8.2%
i 41717
8.2%
g 40456
8.0%
o 29963
 
5.9%
u 28702
 
5.6%
p 1261
 
0.2%
Distinct3
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size4.3 MiB
2024-12-29T11:10:28.974073image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length11
Median length8
Mean length7.6461324
Min length7

Characters and Unicode

Total characters538433
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowritorno
2nd rowritorno
3rd rowritorno
4th rowritorno
5th rowritorno
ValueCountFrequency (%)
garanzia 40456
57.5%
ritorno 28702
40.8%
riparazione 1261
 
1.8%
2024-12-29T11:10:29.265109image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 123890
23.0%
r 100382
18.6%
i 71680
13.3%
n 70419
13.1%
o 58665
10.9%
z 41717
 
7.7%
g 40456
 
7.5%
t 28702
 
5.3%
p 1261
 
0.2%
e 1261
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 538433
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 123890
23.0%
r 100382
18.6%
i 71680
13.3%
n 70419
13.1%
o 58665
10.9%
z 41717
 
7.7%
g 40456
 
7.5%
t 28702
 
5.3%
p 1261
 
0.2%
e 1261
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 538433
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 123890
23.0%
r 100382
18.6%
i 71680
13.3%
n 70419
13.1%
o 58665
10.9%
z 41717
 
7.7%
g 40456
 
7.5%
t 28702
 
5.3%
p 1261
 
0.2%
e 1261
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 538433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 123890
23.0%
r 100382
18.6%
i 71680
13.3%
n 70419
13.1%
o 58665
10.9%
z 41717
 
7.7%
g 40456
 
7.5%
t 28702
 
5.3%
p 1261
 
0.2%
e 1261
 
0.2%

titulo_pt_tipo
Unsupported

Missing70423
Missing (%)100.0%
Memory size550.3 KiB
Distinct12956
Distinct (%)68.9%
Missing543
Missing (%)2.8%
Memory size2.6 MiB
2024-12-29T11:10:29.563626image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length582
Median length460
Mean length76.8201
Min length1

Characters and Unicode

Total characters1445447
Distinct characters131
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10700 ?
Unique (%)56.9%

Sample

1st rowDespués del diagnóstico de HOTLINE
2nd rowDespués del diagnóstico de HOTLINE
3rd rowDespués del diagnóstico de HOTLINE
4th rowCAMBIO CPP EN GARANTIA POR PROBLEMAS COMUNICACION
5th rowTARJETA POTENTE PARA 8 ZONAS
ValueCountFrequency (%)
de 12301
 
5.3%
no 7541
 
3.3%
el 7127
 
3.1%
la 6878
 
3.0%
en 5104
 
2.2%
y 4292
 
1.9%
se 4263
 
1.9%
que 4023
 
1.7%
con 3990
 
1.7%
funciona 2814
 
1.2%
Other values (14919) 171678
74.6%
2024-12-29T11:10:30.075111image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
205989
 
14.3%
e 78367
 
5.4%
a 70344
 
4.9%
A 67014
 
4.6%
E 66103
 
4.6%
o 56965
 
3.9%
n 47987
 
3.3%
O 46573
 
3.2%
N 44349
 
3.1%
r 39104
 
2.7%
Other values (121) 722652
50.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 595509
41.2%
Uppercase Letter 549004
38.0%
Space Separator 205991
 
14.3%
Decimal Number 49618
 
3.4%
Other Punctuation 21147
 
1.5%
Control 17658
 
1.2%
Dash Punctuation 1676
 
0.1%
Open Punctuation 1266
 
0.1%
Close Punctuation 1232
 
0.1%
Other Symbol 1099
 
0.1%
Other values (8) 1247
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 78367
13.2%
a 70344
11.8%
o 56965
9.6%
n 47987
 
8.1%
r 39104
 
6.6%
i 37277
 
6.3%
t 36238
 
6.1%
l 34162
 
5.7%
s 33997
 
5.7%
c 30178
 
5.1%
Other values (28) 130890
22.0%
Uppercase Letter
ValueCountFrequency (%)
A 67014
12.2%
E 66103
12.0%
O 46573
 
8.5%
N 44349
 
8.1%
I 34347
 
6.3%
T 33670
 
6.1%
R 32673
 
6.0%
L 30667
 
5.6%
C 30250
 
5.5%
S 30089
 
5.5%
Other values (28) 133269
24.3%
Other Punctuation
ValueCountFrequency (%)
. 10420
49.3%
, 6212
29.4%
: 1975
 
9.3%
/ 1455
 
6.9%
" 255
 
1.2%
? 225
 
1.1%
% 92
 
0.4%
; 89
 
0.4%
* 85
 
0.4%
\ 84
 
0.4%
Other values (8) 255
 
1.2%
Decimal Number
ValueCountFrequency (%)
0 9874
19.9%
1 7176
14.5%
2 6763
13.6%
6 6188
12.5%
3 4680
9.4%
5 3535
 
7.1%
4 3403
 
6.9%
8 2966
 
6.0%
7 2560
 
5.2%
9 2473
 
5.0%
Math Symbol
ValueCountFrequency (%)
+ 469
74.8%
> 104
 
16.6%
= 36
 
5.7%
< 17
 
2.7%
| 1
 
0.2%
Control
ValueCountFrequency (%)
8855
50.1%
8690
49.2%
113
 
0.6%
Space Separator
ValueCountFrequency (%)
205989
> 99.9%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1673
99.8%
3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1265
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1231
99.9%
] 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
° 1095
99.6%
4
 
0.4%
Other Letter
ValueCountFrequency (%)
º 461
95.6%
ª 21
 
4.4%
Modifier Symbol
ValueCountFrequency (%)
´ 2
66.7%
` 1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 78
100.0%
Initial Punctuation
ValueCountFrequency (%)
25
100.0%
Final Punctuation
ValueCountFrequency (%)
25
100.0%
Format
ValueCountFrequency (%)
6
100.0%
Currency Symbol
ValueCountFrequency (%)
£ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1144995
79.2%
Common 300452
 
20.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 78367
 
6.8%
a 70344
 
6.1%
A 67014
 
5.9%
E 66103
 
5.8%
o 56965
 
5.0%
n 47987
 
4.2%
O 46573
 
4.1%
N 44349
 
3.9%
r 39104
 
3.4%
i 37277
 
3.3%
Other values (68) 590912
51.6%
Common
ValueCountFrequency (%)
205989
68.6%
. 10420
 
3.5%
0 9874
 
3.3%
8855
 
2.9%
8690
 
2.9%
1 7176
 
2.4%
2 6763
 
2.3%
, 6212
 
2.1%
6 6188
 
2.1%
3 4680
 
1.6%
Other values (43) 25605
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1429298
98.9%
None 16086
 
1.1%
Punctuation 59
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
205989
 
14.4%
e 78367
 
5.5%
a 70344
 
4.9%
A 67014
 
4.7%
E 66103
 
4.6%
o 56965
 
4.0%
n 47987
 
3.4%
O 46573
 
3.3%
N 44349
 
3.1%
r 39104
 
2.7%
Other values (83) 706503
49.4%
None
ValueCountFrequency (%)
ó 3799
23.6%
í 2550
15.9%
Ó 1964
12.2%
Í 1323
 
8.2%
á 1194
 
7.4%
é 1184
 
7.4%
° 1095
 
6.8%
ú 896
 
5.6%
º 461
 
2.9%
ñ 367
 
2.3%
Other values (23) 1253
 
7.8%
Punctuation
ValueCountFrequency (%)
25
42.4%
25
42.4%
6
 
10.2%
3
 
5.1%
Letterlike Symbols
ValueCountFrequency (%)
4
100.0%
Distinct5634
Distinct (%)36.1%
Missing3752
Missing (%)19.4%
Memory size1.4 MiB
2024-12-29T11:10:30.326200image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length76
Median length51
Mean length27.055488
Min length1

Characters and Unicode

Total characters422255
Distinct characters104
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3989 ?
Unique (%)25.6%

Sample

1st rowPasarela de comunicaciones HITACHI RPI
2nd rowPuerta de enlace de comunicación
3rd rowCENTRAL DE PRODUCCION
4th row0000
5th rowMANDO
ValueCountFrequency (%)
termostato 4048
 
6.5%
de 3402
 
5.5%
airzone 2990
 
4.8%
central 1776
 
2.9%
radio 1563
 
2.5%
blanco 1425
 
2.3%
cable 1389
 
2.2%
web 1280
 
2.1%
blueface 1260
 
2.0%
servidor 1243
 
2.0%
Other values (2564) 41511
67.1%
2024-12-29T11:10:30.776136image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46338
 
11.0%
A 31677
 
7.5%
E 29936
 
7.1%
O 27825
 
6.6%
T 22251
 
5.3%
R 22182
 
5.3%
I 18379
 
4.4%
N 17075
 
4.0%
L 15748
 
3.7%
C 14488
 
3.4%
Other values (94) 176356
41.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 274083
64.9%
Lowercase Letter 84826
 
20.1%
Space Separator 46338
 
11.0%
Decimal Number 12341
 
2.9%
Other Punctuation 2615
 
0.6%
Dash Punctuation 1233
 
0.3%
Open Punctuation 378
 
0.1%
Close Punctuation 269
 
0.1%
Math Symbol 129
 
< 0.1%
Other Symbol 26
 
< 0.1%
Other values (2) 17
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 31677
11.6%
E 29936
10.9%
O 27825
10.2%
T 22251
 
8.1%
R 22182
 
8.1%
I 18379
 
6.7%
N 17075
 
6.2%
L 15748
 
5.7%
C 14488
 
5.3%
S 10014
 
3.7%
Other values (24) 64508
23.5%
Lowercase Letter
ValueCountFrequency (%)
a 10202
12.0%
e 9738
11.5%
o 9717
11.5%
r 7493
8.8%
t 6405
 
7.6%
n 5622
 
6.6%
i 5447
 
6.4%
l 4593
 
5.4%
c 4443
 
5.2%
d 3764
 
4.4%
Other values (22) 17402
20.5%
Other Punctuation
ValueCountFrequency (%)
. 2020
77.2%
/ 303
 
11.6%
* 132
 
5.0%
, 88
 
3.4%
: 25
 
1.0%
\ 13
 
0.5%
? 10
 
0.4%
" 8
 
0.3%
¿ 5
 
0.2%
' 3
 
0.1%
Other values (5) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 3320
26.9%
6 2294
18.6%
3 1686
13.7%
2 1335
10.8%
8 1282
 
10.4%
5 993
 
8.0%
1 905
 
7.3%
4 417
 
3.4%
7 79
 
0.6%
9 30
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 375
99.2%
[ 3
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 266
98.9%
] 3
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 124
96.1%
> 5
 
3.9%
Other Symbol
ValueCountFrequency (%)
20
76.9%
° 6
 
23.1%
Other Letter
ValueCountFrequency (%)
º 15
93.8%
ª 1
 
6.2%
Space Separator
ValueCountFrequency (%)
46338
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1233
100.0%
Control
ValueCountFrequency (%)
 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 358925
85.0%
Common 63330
 
15.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 31677
 
8.8%
E 29936
 
8.3%
O 27825
 
7.8%
T 22251
 
6.2%
R 22182
 
6.2%
I 18379
 
5.1%
N 17075
 
4.8%
L 15748
 
4.4%
C 14488
 
4.0%
a 10202
 
2.8%
Other values (58) 149162
41.6%
Common
ValueCountFrequency (%)
46338
73.2%
0 3320
 
5.2%
6 2294
 
3.6%
. 2020
 
3.2%
3 1686
 
2.7%
2 1335
 
2.1%
8 1282
 
2.0%
- 1233
 
1.9%
5 993
 
1.6%
1 905
 
1.4%
Other values (26) 1924
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420365
99.6%
None 1870
 
0.4%
Letterlike Symbols 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46338
 
11.0%
A 31677
 
7.5%
E 29936
 
7.1%
O 27825
 
6.6%
T 22251
 
5.3%
R 22182
 
5.3%
I 18379
 
4.4%
N 17075
 
4.1%
L 15748
 
3.7%
C 14488
 
3.4%
Other values (72) 174466
41.5%
None
ValueCountFrequency (%)
Ó 867
46.4%
ó 407
21.8%
É 208
 
11.1%
á 134
 
7.2%
Á 71
 
3.8%
é 69
 
3.7%
Í 26
 
1.4%
Ú 23
 
1.2%
º 15
 
0.8%
Ø 13
 
0.7%
Other values (11) 37
 
2.0%
Letterlike Symbols
ValueCountFrequency (%)
20
100.0%
Distinct13486
Distinct (%)69.7%
Missing1
Missing (%)< 0.1%
Memory size2.1 MiB
2024-12-29T11:10:31.384363image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length314
Median length257
Mean length46.959655
Min length1

Characters and Unicode

Total characters909045
Distinct characters124
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11961 ?
Unique (%)61.8%

Sample

1st rowNo más comunicación, asociación WIFI imposible.
2nd rowproblema de comunicacion
3rd rowproblema de comunicacion
4th rowfallo en comunicacion central de produccion
5th rowRAS
ValueCountFrequency (%)
de 7187
 
4.9%
no 6144
 
4.2%
el 4753
 
3.3%
la 4201
 
2.9%
en 3239
 
2.2%
funciona 2749
 
1.9%
se 2676
 
1.8%
con 2458
 
1.7%
termostato 2263
 
1.6%
y 2083
 
1.4%
Other values (12287) 107942
74.1%
2024-12-29T11:10:31.906909image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124248
 
13.7%
A 46569
 
5.1%
E 46206
 
5.1%
e 43957
 
4.8%
a 40074
 
4.4%
O 35680
 
3.9%
N 34147
 
3.8%
o 32876
 
3.6%
n 26951
 
3.0%
I 25499
 
2.8%
Other values (114) 452838
49.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 387929
42.7%
Lowercase Letter 336655
37.0%
Space Separator 124250
 
13.7%
Decimal Number 36352
 
4.0%
Other Punctuation 12065
 
1.3%
Control 7771
 
0.9%
Other Symbol 1050
 
0.1%
Dash Punctuation 920
 
0.1%
Open Punctuation 674
 
0.1%
Close Punctuation 656
 
0.1%
Other values (7) 723
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 43957
13.1%
a 40074
11.9%
o 32876
9.8%
n 26951
 
8.0%
r 22325
 
6.6%
t 21493
 
6.4%
i 21277
 
6.3%
l 19515
 
5.8%
c 17810
 
5.3%
s 17386
 
5.2%
Other values (27) 72991
21.7%
Uppercase Letter
ValueCountFrequency (%)
A 46569
12.0%
E 46206
11.9%
O 35680
 
9.2%
N 34147
 
8.8%
I 25499
 
6.6%
T 24328
 
6.3%
R 23754
 
6.1%
C 21393
 
5.5%
L 20548
 
5.3%
S 19517
 
5.0%
Other values (25) 90288
23.3%
Other Punctuation
ValueCountFrequency (%)
. 6219
51.5%
, 3475
28.8%
: 944
 
7.8%
/ 600
 
5.0%
\ 156
 
1.3%
* 156
 
1.3%
" 141
 
1.2%
? 140
 
1.2%
% 63
 
0.5%
¿ 50
 
0.4%
Other values (7) 121
 
1.0%
Decimal Number
ValueCountFrequency (%)
0 6186
17.0%
1 5340
14.7%
2 4934
13.6%
6 4028
11.1%
3 3554
9.8%
4 2785
7.7%
5 2708
7.4%
8 2404
 
6.6%
7 2235
 
6.1%
9 2178
 
6.0%
Math Symbol
ValueCountFrequency (%)
+ 193
75.4%
> 40
 
15.6%
= 17
 
6.6%
< 6
 
2.3%
Control
ValueCountFrequency (%)
3937
50.7%
3789
48.8%
45
 
0.6%
Modifier Symbol
ValueCountFrequency (%)
´ 1
33.3%
¨ 1
33.3%
` 1
33.3%
Space Separator
ValueCountFrequency (%)
124248
> 99.9%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 918
99.8%
2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 672
99.7%
[ 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 654
99.7%
] 2
 
0.3%
Other Letter
ValueCountFrequency (%)
º 274
95.8%
ª 12
 
4.2%
Other Symbol
ValueCountFrequency (%)
° 1050
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 158
100.0%
Format
ValueCountFrequency (%)
16
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 724870
79.7%
Common 184175
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 46569
 
6.4%
E 46206
 
6.4%
e 43957
 
6.1%
a 40074
 
5.5%
O 35680
 
4.9%
N 34147
 
4.7%
o 32876
 
4.5%
n 26951
 
3.7%
I 25499
 
3.5%
T 24328
 
3.4%
Other values (64) 368583
50.8%
Common
ValueCountFrequency (%)
124248
67.5%
. 6219
 
3.4%
0 6186
 
3.4%
1 5340
 
2.9%
2 4934
 
2.7%
6 4028
 
2.2%
3937
 
2.1%
3789
 
2.1%
3 3554
 
1.9%
, 3475
 
1.9%
Other values (40) 18465
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 898373
98.8%
None 10650
 
1.2%
Punctuation 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124248
 
13.8%
A 46569
 
5.2%
E 46206
 
5.1%
e 43957
 
4.9%
a 40074
 
4.5%
O 35680
 
4.0%
N 34147
 
3.8%
o 32876
 
3.7%
n 26951
 
3.0%
I 25499
 
2.8%
Other values (81) 442166
49.2%
None
ValueCountFrequency (%)
ó 2224
20.9%
í 1464
13.7%
Ó 1375
12.9%
Í 1139
10.7%
° 1050
9.9%
á 750
 
7.0%
é 604
 
5.7%
ú 523
 
4.9%
º 274
 
2.6%
Ú 256
 
2.4%
Other values (19) 991
9.3%
Punctuation
ValueCountFrequency (%)
16
72.7%
2
 
9.1%
2
 
9.1%
2
 
9.1%
Distinct1141
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2024-12-29T11:10:32.134619image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length15
Median length14
Mean length12.179348
Min length3

Characters and Unicode

Total characters235780
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique591 ?
Unique (%)3.1%

Sample

1st rowAZXWSCLOUDWIFI
2nd rowAZX6QADAPTHIT
3rd rowAZX6QADAPTHIT
4th rowAZX6CCP
5th rowAZCE6EXP8Z
ValueCountFrequency (%)
azce6thinkrb 2086
 
10.8%
azce6bluefacecb 1690
 
8.7%
azce6bluezerocb 815
 
4.2%
azx6wsc5ger 747
 
3.9%
azce6flexa3 603
 
3.1%
azpv8cb1iaq 520
 
2.7%
azce6ibpro6e 457
 
2.4%
azdi6bluefacecb 411
 
2.1%
azce6thinkcb 384
 
2.0%
azx6gtcda1 383
 
2.0%
Other values (1131) 11263
58.2%
2024-12-29T11:10:32.518879image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 27544
 
11.7%
C 23649
 
10.0%
E 20236
 
8.6%
Z 20117
 
8.5%
6 17025
 
7.2%
B 14706
 
6.2%
I 10314
 
4.4%
T 8956
 
3.8%
R 8624
 
3.7%
L 6658
 
2.8%
Other values (29) 77951
33.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 203398
86.3%
Decimal Number 32146
 
13.6%
Dash Punctuation 133
 
0.1%
Connector Punctuation 55
 
< 0.1%
Space Separator 48
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 27544
13.5%
C 23649
11.6%
E 20236
 
9.9%
Z 20117
 
9.9%
B 14706
 
7.2%
I 10314
 
5.1%
T 8956
 
4.4%
R 8624
 
4.2%
L 6658
 
3.3%
N 6538
 
3.2%
Other values (16) 56056
27.6%
Decimal Number
ValueCountFrequency (%)
6 17025
53.0%
0 5117
 
15.9%
1 3613
 
11.2%
5 1649
 
5.1%
3 1584
 
4.9%
8 1532
 
4.8%
2 1090
 
3.4%
4 333
 
1.0%
7 190
 
0.6%
9 13
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 55
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 203398
86.3%
Common 32382
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 27544
13.5%
C 23649
11.6%
E 20236
 
9.9%
Z 20117
 
9.9%
B 14706
 
7.2%
I 10314
 
5.1%
T 8956
 
4.4%
R 8624
 
4.2%
L 6658
 
3.3%
N 6538
 
3.2%
Other values (16) 56056
27.6%
Common
ValueCountFrequency (%)
6 17025
52.6%
0 5117
 
15.8%
1 3613
 
11.2%
5 1649
 
5.1%
3 1584
 
4.9%
8 1532
 
4.7%
2 1090
 
3.4%
4 333
 
1.0%
7 190
 
0.6%
- 133
 
0.4%
Other values (3) 116
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 27544
 
11.7%
C 23649
 
10.0%
E 20236
 
8.6%
Z 20117
 
8.5%
6 17025
 
7.2%
B 14706
 
6.2%
I 10314
 
4.4%
T 8956
 
3.8%
R 8624
 
3.7%
L 6658
 
2.8%
Other values (29) 77951
33.1%

Fuzzy_Score
Real number (ℝ)

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.437574
Minimum85
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size151.4 KiB
2024-12-29T11:10:32.663035image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Quantile statistics

Minimum85
5-th percentile95
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.0492478
Coefficient of variation (CV)0.020608385
Kurtosis16.190582
Mean99.437574
Median Absolute Deviation (MAD)0
Skewness-3.9921457
Sum1925012
Variance4.1994167
MonotonicityNot monotonic
2024-12-29T11:10:32.798820image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
100 17731
91.6%
96 349
 
1.8%
92 231
 
1.2%
97 229
 
1.2%
91 191
 
1.0%
95 184
 
1.0%
93 173
 
0.9%
90 133
 
0.7%
86 43
 
0.2%
87 38
 
0.2%
Other values (4) 57
 
0.3%
ValueCountFrequency (%)
85 10
 
0.1%
86 43
 
0.2%
87 38
 
0.2%
88 19
 
0.1%
89 27
 
0.1%
90 133
0.7%
91 191
1.0%
92 231
1.2%
93 173
0.9%
94 1
 
< 0.1%
ValueCountFrequency (%)
100 17731
91.6%
97 229
 
1.2%
96 349
 
1.8%
95 184
 
1.0%
94 1
 
< 0.1%
93 173
 
0.9%
92 231
 
1.2%
91 191
 
1.0%
90 133
 
0.7%
89 27
 
0.1%

CODART
Text

Distinct1141
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2024-12-29T11:10:33.028107image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length15
Median length14
Mean length12.179348
Min length3

Characters and Unicode

Total characters235780
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique591 ?
Unique (%)3.1%

Sample

1st rowAZXWSCLOUDWIFI
2nd rowAZX6QADAPTHIT
3rd rowAZX6QADAPTHIT
4th rowAZX6CCP
5th rowAZCE6EXP8Z
ValueCountFrequency (%)
azce6thinkrb 2086
 
10.8%
azce6bluefacecb 1690
 
8.7%
azce6bluezerocb 815
 
4.2%
azx6wsc5ger 747
 
3.9%
azce6flexa3 603
 
3.1%
azpv8cb1iaq 520
 
2.7%
azce6ibpro6e 457
 
2.4%
azdi6bluefacecb 411
 
2.1%
azce6thinkcb 384
 
2.0%
azx6gtcda1 383
 
2.0%
Other values (1131) 11263
58.2%
2024-12-29T11:10:33.440601image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 27544
 
11.7%
C 23649
 
10.0%
E 20236
 
8.6%
Z 20117
 
8.5%
6 17025
 
7.2%
B 14706
 
6.2%
I 10314
 
4.4%
T 8956
 
3.8%
R 8624
 
3.7%
L 6658
 
2.8%
Other values (29) 77951
33.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 203398
86.3%
Decimal Number 32146
 
13.6%
Dash Punctuation 133
 
0.1%
Connector Punctuation 55
 
< 0.1%
Space Separator 48
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 27544
13.5%
C 23649
11.6%
E 20236
 
9.9%
Z 20117
 
9.9%
B 14706
 
7.2%
I 10314
 
5.1%
T 8956
 
4.4%
R 8624
 
4.2%
L 6658
 
3.3%
N 6538
 
3.2%
Other values (16) 56056
27.6%
Decimal Number
ValueCountFrequency (%)
6 17025
53.0%
0 5117
 
15.9%
1 3613
 
11.2%
5 1649
 
5.1%
3 1584
 
4.9%
8 1532
 
4.8%
2 1090
 
3.4%
4 333
 
1.0%
7 190
 
0.6%
9 13
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 55
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 203398
86.3%
Common 32382
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 27544
13.5%
C 23649
11.6%
E 20236
 
9.9%
Z 20117
 
9.9%
B 14706
 
7.2%
I 10314
 
5.1%
T 8956
 
4.4%
R 8624
 
4.2%
L 6658
 
3.3%
N 6538
 
3.2%
Other values (16) 56056
27.6%
Common
ValueCountFrequency (%)
6 17025
52.6%
0 5117
 
15.8%
1 3613
 
11.2%
5 1649
 
5.1%
3 1584
 
4.9%
8 1532
 
4.7%
2 1090
 
3.4%
4 333
 
1.0%
7 190
 
0.6%
- 133
 
0.4%
Other values (3) 116
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 27544
 
11.7%
C 23649
 
10.0%
E 20236
 
8.6%
Z 20117
 
8.5%
6 17025
 
7.2%
B 14706
 
6.2%
I 10314
 
4.4%
T 8956
 
3.8%
R 8624
 
3.7%
L 6658
 
2.8%
Other values (29) 77951
33.1%
Distinct1134
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
2024-12-29T11:10:33.706981image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length98
Median length88
Mean length49.520068
Min length5

Characters and Unicode

Total characters958659
Distinct characters81
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique587 ?
Unique (%)3.0%

Sample

1st rowWebserver Airzone Cloud Wi-Fi (2013)
2nd rowPasarela comunicaciones Airzone-Hitachi RPI
3rd rowPasarela comunicaciones Airzone-Hitachi RPI
4th rowCentral de control de producción Airzone
5th rowMódulo de expansión Airzone 2 zonas (7 y 8)
ValueCountFrequency (%)
airzone 15405
 
10.9%
blanco 7140
 
5.1%
termostato 7085
 
5.0%
de 6635
 
4.7%
ce6 6030
 
4.3%
8z 5752
 
4.1%
cable 5347
 
3.8%
central 3778
 
2.7%
blueface 3650
 
2.6%
think 2945
 
2.1%
Other values (709) 77311
54.8%
2024-12-29T11:10:34.186830image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121720
 
12.7%
o 85371
 
8.9%
e 76600
 
8.0%
a 60078
 
6.3%
r 58041
 
6.1%
n 50662
 
5.3%
i 45513
 
4.7%
l 40169
 
4.2%
c 35230
 
3.7%
t 32947
 
3.4%
Other values (71) 352328
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 640859
66.8%
Uppercase Letter 124653
 
13.0%
Space Separator 121720
 
12.7%
Decimal Number 43003
 
4.5%
Open Punctuation 8453
 
0.9%
Close Punctuation 8453
 
0.9%
Other Punctuation 5865
 
0.6%
Dash Punctuation 5038
 
0.5%
Math Symbol 530
 
0.1%
Other Letter 64
 
< 0.1%
Other values (2) 21
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 85371
13.3%
e 76600
12.0%
a 60078
9.4%
r 58041
9.1%
n 50662
 
7.9%
i 45513
 
7.1%
l 40169
 
6.3%
c 35230
 
5.5%
t 32947
 
5.1%
m 24768
 
3.9%
Other values (21) 131480
20.5%
Uppercase Letter
ValueCountFrequency (%)
A 23291
18.7%
C 13649
10.9%
E 13042
10.5%
T 12556
10.1%
Z 12418
10.0%
R 5132
 
4.1%
I 4865
 
3.9%
B 4795
 
3.8%
M 4618
 
3.7%
P 4231
 
3.4%
Other values (16) 26056
20.9%
Decimal Number
ValueCountFrequency (%)
6 10029
23.3%
0 8710
20.3%
8 7538
17.5%
3 5156
12.0%
2 5082
11.8%
5 2537
 
5.9%
4 1873
 
4.4%
1 1797
 
4.2%
7 254
 
0.6%
9 27
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 4382
74.7%
/ 1181
 
20.1%
* 182
 
3.1%
, 100
 
1.7%
" 19
 
0.3%
% 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
121720
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8453
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8453
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5038
100.0%
Math Symbol
ValueCountFrequency (%)
+ 530
100.0%
Other Letter
ValueCountFrequency (%)
º 64
100.0%
Other Symbol
ValueCountFrequency (%)
° 16
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 765576
79.9%
Common 193083
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 85371
 
11.2%
e 76600
 
10.0%
a 60078
 
7.8%
r 58041
 
7.6%
n 50662
 
6.6%
i 45513
 
5.9%
l 40169
 
5.2%
c 35230
 
4.6%
t 32947
 
4.3%
m 24768
 
3.2%
Other values (48) 256197
33.5%
Common
ValueCountFrequency (%)
121720
63.0%
6 10029
 
5.2%
0 8710
 
4.5%
( 8453
 
4.4%
) 8453
 
4.4%
8 7538
 
3.9%
3 5156
 
2.7%
2 5082
 
2.6%
- 5038
 
2.6%
. 4382
 
2.3%
Other values (13) 8522
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 956694
99.8%
None 1965
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121720
 
12.7%
o 85371
 
8.9%
e 76600
 
8.0%
a 60078
 
6.3%
r 58041
 
6.1%
n 50662
 
5.3%
i 45513
 
4.8%
l 40169
 
4.2%
c 35230
 
3.7%
t 32947
 
3.4%
Other values (64) 350363
36.6%
None
ValueCountFrequency (%)
ó 1296
66.0%
é 412
 
21.0%
á 120
 
6.1%
º 64
 
3.3%
í 51
 
2.6%
° 16
 
0.8%
ú 6
 
0.3%

CAR1
Text

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-12-29T11:10:34.301317image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters19359
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 18733
96.8%
6 251
 
1.3%
2 233
 
1.2%
5 96
 
0.5%
3 43
 
0.2%
4 3
 
< 0.1%
2024-12-29T11:10:34.535922image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18733
96.8%
6 251
 
1.3%
2 233
 
1.2%
5 96
 
0.5%
3 43
 
0.2%
4 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19359
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18733
96.8%
6 251
 
1.3%
2 233
 
1.2%
5 96
 
0.5%
3 43
 
0.2%
4 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 19359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18733
96.8%
6 251
 
1.3%
2 233
 
1.2%
5 96
 
0.5%
3 43
 
0.2%
4 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18733
96.8%
6 251
 
1.3%
2 233
 
1.2%
5 96
 
0.5%
3 43
 
0.2%
4 3
 
< 0.1%

CAR2
Text

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-12-29T11:10:34.690769image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9637895
Min length1

Characters and Unicode

Total characters57376
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row260
2nd row260
3rd row260
4th row260
5th row250
ValueCountFrequency (%)
250 7956
41.1%
260 4055
20.9%
251 2104
 
10.9%
264 1183
 
6.1%
269 1115
 
5.8%
253 777
 
4.0%
17 558
 
2.9%
252 356
 
1.8%
270 344
 
1.8%
255 292
 
1.5%
Other values (16) 619
 
3.2%
2024-12-29T11:10:35.090871image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19304
33.6%
0 12378
21.6%
5 11875
20.7%
6 6659
 
11.6%
1 2748
 
4.8%
4 1430
 
2.5%
9 1131
 
2.0%
7 932
 
1.6%
3 916
 
1.6%
8 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57376
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19304
33.6%
0 12378
21.6%
5 11875
20.7%
6 6659
 
11.6%
1 2748
 
4.8%
4 1430
 
2.5%
9 1131
 
2.0%
7 932
 
1.6%
3 916
 
1.6%
8 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 57376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19304
33.6%
0 12378
21.6%
5 11875
20.7%
6 6659
 
11.6%
1 2748
 
4.8%
4 1430
 
2.5%
9 1131
 
2.0%
7 932
 
1.6%
3 916
 
1.6%
8 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19304
33.6%
0 12378
21.6%
5 11875
20.7%
6 6659
 
11.6%
1 2748
 
4.8%
4 1430
 
2.5%
9 1131
 
2.0%
7 932
 
1.6%
3 916
 
1.6%
8 3
 
< 0.1%

CAR3
Text

Distinct31
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-12-29T11:10:35.250550image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.000155
Min length2

Characters and Unicode

Total characters38721
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row93
2nd row49
3rd row49
4th row92
5th row90
ValueCountFrequency (%)
91 7068
36.5%
80 2975
15.4%
90 2332
 
12.0%
93 1875
 
9.7%
49 1679
 
8.7%
95 823
 
4.3%
31 554
 
2.9%
92 384
 
2.0%
98 364
 
1.9%
19 288
 
1.5%
Other values (21) 1017
 
5.3%
2024-12-29T11:10:35.550796image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 15169
39.2%
1 7943
20.5%
0 5313
 
13.7%
8 3893
 
10.1%
3 2527
 
6.5%
4 2166
 
5.6%
5 877
 
2.3%
2 619
 
1.6%
7 203
 
0.5%
6 11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38721
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 15169
39.2%
1 7943
20.5%
0 5313
 
13.7%
8 3893
 
10.1%
3 2527
 
6.5%
4 2166
 
5.6%
5 877
 
2.3%
2 619
 
1.6%
7 203
 
0.5%
6 11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 38721
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 15169
39.2%
1 7943
20.5%
0 5313
 
13.7%
8 3893
 
10.1%
3 2527
 
6.5%
4 2166
 
5.6%
5 877
 
2.3%
2 619
 
1.6%
7 203
 
0.5%
6 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38721
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 15169
39.2%
1 7943
20.5%
0 5313
 
13.7%
8 3893
 
10.1%
3 2527
 
6.5%
4 2166
 
5.6%
5 877
 
2.3%
2 619
 
1.6%
7 203
 
0.5%
6 11
 
< 0.1%

CAR4
Text

Distinct48
Distinct (%)0.5%
Missing9174
Missing (%)47.4%
Memory size868.8 KiB
2024-12-29T11:10:35.714883image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.5116348
Min length1

Characters and Unicode

Total characters15396
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 3560
35.0%
2 2845
27.9%
204 754
 
7.4%
108 695
 
6.8%
3 495
 
4.9%
92 333
 
3.3%
32 220
 
2.2%
140 190
 
1.9%
97 178
 
1.7%
109 137
 
1.3%
Other values (38) 778
 
7.6%
2024-12-29T11:10:36.040683image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4918
31.9%
2 4170
27.1%
0 2001
13.0%
4 1027
 
6.7%
3 914
 
5.9%
8 877
 
5.7%
9 876
 
5.7%
7 376
 
2.4%
6 218
 
1.4%
5 19
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15396
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4918
31.9%
2 4170
27.1%
0 2001
13.0%
4 1027
 
6.7%
3 914
 
5.9%
8 877
 
5.7%
9 876
 
5.7%
7 376
 
2.4%
6 218
 
1.4%
5 19
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4918
31.9%
2 4170
27.1%
0 2001
13.0%
4 1027
 
6.7%
3 914
 
5.9%
8 877
 
5.7%
9 876
 
5.7%
7 376
 
2.4%
6 218
 
1.4%
5 19
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4918
31.9%
2 4170
27.1%
0 2001
13.0%
4 1027
 
6.7%
3 914
 
5.9%
8 877
 
5.7%
9 876
 
5.7%
7 376
 
2.4%
6 218
 
1.4%
5 19
 
0.1%
Distinct17118
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size5.8 MiB
2024-12-29T11:10:36.325614image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length909
Median length675
Mean length145.43442
Min length26

Characters and Unicode

Total characters2815465
Distinct characters136
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16005 ?
Unique (%)82.7%

Sample

1st rowDespués del diagnóstico de HOTLINE No más comunicación, asociación WIFI imposible.
2nd rowDespués del diagnóstico de HOTLINE Pasarela de comunicaciones HITACHI RPI problema de comunicacion
3rd rowDespués del diagnóstico de HOTLINE Puerta de enlace de comunicación problema de comunicacion
4th rowCAMBIO CPP EN GARANTIA POR PROBLEMAS COMUNICACION CENTRAL DE PRODUCCION fallo en comunicacion central de produccion
5th rowTARJETA POTENTE PARA 8 ZONAS 0000 RAS
ValueCountFrequency (%)
de 22890
 
5.2%
no 13707
 
3.1%
el 11995
 
2.7%
la 11279
 
2.6%
termostato 8898
 
2.0%
en 8848
 
2.0%
se 6942
 
1.6%
con 6750
 
1.5%
y 6531
 
1.5%
que 6115
 
1.4%
Other values (19188) 333638
76.2%
2024-12-29T11:10:36.810848image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
415293
 
14.8%
A 145260
 
5.2%
E 142245
 
5.1%
e 132062
 
4.7%
a 120620
 
4.3%
O 110078
 
3.9%
o 99558
 
3.5%
N 95571
 
3.4%
n 80560
 
2.9%
T 80249
 
2.9%
Other values (126) 1393969
49.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1211016
43.0%
Lowercase Letter 1016990
36.1%
Space Separator 415297
 
14.8%
Decimal Number 98311
 
3.5%
Other Punctuation 35827
 
1.3%
Control 25430
 
0.9%
Dash Punctuation 3829
 
0.1%
Open Punctuation 2318
 
0.1%
Other Symbol 2175
 
0.1%
Close Punctuation 2157
 
0.1%
Other values (8) 2115
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 132062
13.0%
a 120620
11.9%
o 99558
9.8%
n 80560
 
7.9%
r 68922
 
6.8%
t 64136
 
6.3%
i 64001
 
6.3%
l 58270
 
5.7%
s 54820
 
5.4%
c 52431
 
5.2%
Other values (30) 221610
21.8%
Uppercase Letter
ValueCountFrequency (%)
A 145260
12.0%
E 142245
11.7%
O 110078
 
9.1%
N 95571
 
7.9%
T 80249
 
6.6%
R 78609
 
6.5%
I 78225
 
6.5%
L 66963
 
5.5%
C 66131
 
5.5%
S 59620
 
4.9%
Other values (29) 288065
23.8%
Other Punctuation
ValueCountFrequency (%)
. 18659
52.1%
, 9775
27.3%
: 2944
 
8.2%
/ 2358
 
6.6%
" 404
 
1.1%
? 375
 
1.0%
* 373
 
1.0%
\ 253
 
0.7%
% 158
 
0.4%
¿ 138
 
0.4%
Other values (8) 390
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 19380
19.7%
1 13421
13.7%
2 13032
13.3%
6 12510
12.7%
3 9920
10.1%
5 7236
 
7.4%
8 6652
 
6.8%
4 6605
 
6.7%
7 4874
 
5.0%
9 4681
 
4.8%
Math Symbol
ValueCountFrequency (%)
+ 786
77.7%
> 149
 
14.7%
= 53
 
5.2%
< 23
 
2.3%
| 1
 
0.1%
Control
ValueCountFrequency (%)
12792
50.3%
12479
49.1%
158
 
0.6%
 1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 3
50.0%
` 2
33.3%
¨ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
415293
> 99.9%
  4
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3824
99.9%
5
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2312
99.7%
[ 6
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2151
99.7%
] 6
 
0.3%
Other Symbol
ValueCountFrequency (%)
° 2151
98.9%
24
 
1.1%
Other Letter
ValueCountFrequency (%)
º 750
95.7%
ª 34
 
4.3%
Connector Punctuation
ValueCountFrequency (%)
_ 236
100.0%
Initial Punctuation
ValueCountFrequency (%)
27
100.0%
Final Punctuation
ValueCountFrequency (%)
27
100.0%
Format
ValueCountFrequency (%)
22
100.0%
Currency Symbol
ValueCountFrequency (%)
£ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2228790
79.2%
Common 586675
 
20.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 145260
 
6.5%
E 142245
 
6.4%
e 132062
 
5.9%
a 120620
 
5.4%
O 110078
 
4.9%
o 99558
 
4.5%
N 95571
 
4.3%
n 80560
 
3.6%
T 80249
 
3.6%
R 78609
 
3.5%
Other values (71) 1143978
51.3%
Common
ValueCountFrequency (%)
415293
70.8%
0 19380
 
3.3%
. 18659
 
3.2%
1 13421
 
2.3%
2 13032
 
2.2%
12792
 
2.2%
6 12510
 
2.1%
12479
 
2.1%
3 9920
 
1.7%
, 9775
 
1.7%
Other values (45) 49414
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2786754
99.0%
None 28606
 
1.0%
Punctuation 81
 
< 0.1%
Letterlike Symbols 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
415293
 
14.9%
A 145260
 
5.2%
E 142245
 
5.1%
e 132062
 
4.7%
a 120620
 
4.3%
O 110078
 
4.0%
o 99558
 
3.6%
N 95571
 
3.4%
n 80560
 
2.9%
T 80249
 
2.9%
Other values (83) 1365258
49.0%
None
ValueCountFrequency (%)
ó 6430
22.5%
Ó 4206
14.7%
í 4022
14.1%
Í 2488
 
8.7%
° 2151
 
7.5%
á 2078
 
7.3%
é 1857
 
6.5%
ú 1424
 
5.0%
º 750
 
2.6%
É 730
 
2.6%
Other values (28) 2470
 
8.6%
Punctuation
ValueCountFrequency (%)
27
33.3%
27
33.3%
22
27.2%
5
 
6.2%
Letterlike Symbols
ValueCountFrequency (%)
24
100.0%
Distinct16800
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size3.3 MiB
2024-12-29T11:10:37.105636image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Length

Max length618
Median length474
Mean length110.86373
Min length9

Characters and Unicode

Total characters2146211
Distinct characters73
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15550 ?
Unique (%)80.3%

Sample

1st rowdiagnostico hotline comunicacion asociacion wifi imposible
2nd rowdiagnostico hotline pasarela comunicaciones hitachi rpi problema comunicacion
3rd rowdiagnostico hotline puerta enlace comunicacion problema comunicacion
4th rowcambio cpp garantia problemas comunicacion central produccion fallo comunicacion central produccion
5th rowtarjeta potente 8 zonas 0000 ras
ValueCountFrequency (%)
termostato 8909
 
3.2%
funciona 5575
 
2.0%
airzone 4585
 
1.7%
central 3566
 
1.3%
garantia 3306
 
1.2%
motor 2991
 
1.1%
radio 2944
 
1.1%
blueface 2916
 
1.1%
n 2651
 
1.0%
cliente 2202
 
0.8%
Other values (17817) 235263
85.6%
2024-12-29T11:10:37.605696image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255549
11.9%
a 222377
 
10.4%
e 189516
 
8.8%
o 173477
 
8.1%
i 140020
 
6.5%
t 134114
 
6.2%
r 131509
 
6.1%
n 128549
 
6.0%
c 108204
 
5.0%
l 86331
 
4.0%
Other values (63) 576565
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1781969
83.0%
Space Separator 255549
 
11.9%
Decimal Number 98311
 
4.6%
Other Punctuation 4119
 
0.2%
Other Symbol 2175
 
0.1%
Dash Punctuation 2010
 
0.1%
Math Symbol 1012
 
< 0.1%
Other Letter 784
 
< 0.1%
Connector Punctuation 164
 
< 0.1%
Close Punctuation 45
 
< 0.1%
Other values (5) 73
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 222377
12.5%
e 189516
10.6%
o 173477
9.7%
i 140020
 
7.9%
t 134114
 
7.5%
r 131509
 
7.4%
n 128549
 
7.2%
c 108204
 
6.1%
l 86331
 
4.8%
s 83085
 
4.7%
Other values (17) 384787
21.6%
Other Punctuation
ValueCountFrequency (%)
. 2454
59.6%
/ 844
 
20.5%
\ 237
 
5.8%
: 166
 
4.0%
% 157
 
3.8%
" 104
 
2.5%
, 81
 
2.0%
@ 45
 
1.1%
' 16
 
0.4%
* 5
 
0.1%
Other values (5) 10
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 19380
19.7%
1 13421
13.7%
2 13032
13.3%
6 12510
12.7%
3 9920
10.1%
5 7236
 
7.4%
8 6652
 
6.8%
4 6605
 
6.7%
7 4874
 
5.0%
9 4681
 
4.8%
Math Symbol
ValueCountFrequency (%)
+ 786
77.7%
> 149
 
14.7%
= 53
 
5.2%
< 23
 
2.3%
| 1
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
´ 3
50.0%
` 2
33.3%
¨ 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
° 2151
98.9%
24
 
1.1%
Other Letter
ValueCountFrequency (%)
º 750
95.7%
ª 34
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 41
95.3%
[ 2
 
4.7%
Space Separator
ValueCountFrequency (%)
255549
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2010
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 164
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Format
ValueCountFrequency (%)
22
100.0%
Currency Symbol
ValueCountFrequency (%)
£ 1
100.0%
Control
ValueCountFrequency (%)
 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1782753
83.1%
Common 363458
 
16.9%

Most frequent character per script

Common
ValueCountFrequency (%)
255549
70.3%
0 19380
 
5.3%
1 13421
 
3.7%
2 13032
 
3.6%
6 12510
 
3.4%
3 9920
 
2.7%
5 7236
 
2.0%
8 6652
 
1.8%
4 6605
 
1.8%
7 4874
 
1.3%
Other values (34) 14279
 
3.9%
Latin
ValueCountFrequency (%)
a 222377
12.5%
e 189516
10.6%
o 173477
9.7%
i 140020
 
7.9%
t 134114
 
7.5%
r 131509
 
7.4%
n 128549
 
7.2%
c 108204
 
6.1%
l 86331
 
4.8%
s 83085
 
4.7%
Other values (19) 385571
21.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2143206
99.9%
None 2959
 
0.1%
Letterlike Symbols 24
 
< 0.1%
Punctuation 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
255549
11.9%
a 222377
 
10.4%
e 189516
 
8.8%
o 173477
 
8.1%
i 140020
 
6.5%
t 134114
 
6.3%
r 131509
 
6.1%
n 128549
 
6.0%
c 108204
 
5.0%
l 86331
 
4.0%
Other values (51) 573560
26.8%
None
ValueCountFrequency (%)
° 2151
72.7%
º 750
 
25.3%
ª 34
 
1.1%
ø 16
 
0.5%
´ 3
 
0.1%
¨ 1
 
< 0.1%
£ 1
 
< 0.1%
 1
 
< 0.1%
· 1
 
< 0.1%
¡ 1
 
< 0.1%
Letterlike Symbols
ValueCountFrequency (%)
24
100.0%
Punctuation
ValueCountFrequency (%)
22
100.0%

Interactions

Raw Dataset Profile

2024-12-29T11:09:09.463808image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:36.770996image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:38.380959image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:40.126468image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:42.212944image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:44.403583image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.776330image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.817009image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:51.621723image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:55.376838image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.501403image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.929122image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.986709image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.084286image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.404812image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:09.618397image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:36.867456image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.490758image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.223406image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.330805image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:44.555874image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.897345image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.160554image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


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Raw Dataset Profile

2024-12-29T11:08:51.802982image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:55.572363image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.612414image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.046279image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.105423image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.209555image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.542668image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:09.771976image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:36.988893image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.621361image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.338727image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.462822image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:44.841009image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.031559image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.281720image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:52.085585image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:55.803146image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.706807image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.182785image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.240939image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.357153image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.712737image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:10.401413image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.091809image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.728487image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.432718image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.577438image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.087654image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.148770image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.387749image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:52.235904image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:55.971600image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.799401image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.294304image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.356716image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.491903image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.847999image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:10.651845image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.195538image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.837775image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.539643image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.695169image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.238627image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.274607image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.498815image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:52.606967image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:56.124666image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.909400image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.408099image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.474233image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.629131image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.988732image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:10.912467image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.305222image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.950841image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.842171image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.813189image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.380010image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.439463image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.623039image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:52.808883image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:56.274156image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:59.082075image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.524109image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.598995image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.761925image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.120638image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

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Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:11.128580image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.414751image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.071763image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:40.952041image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.935295image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.525703image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.576319image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.755511image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:52.995454image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:56.739524image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:59.202648image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.650623image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.730806image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:05.892495image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.253598image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:11.555879image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.507884image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.180747image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.047305image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.043590image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.672795image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.699162image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:49.868557image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:53.128765image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:56.887937image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:59.321414image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.763159image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.851318image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.006562image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.370582image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:11.874071image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.615919image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.297737image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.153559image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.159065image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.825615image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.825901image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:50.089501image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:53.538200image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:57.053782image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:59.828901image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.874380image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:03.982782image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.139062image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.494034image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:12.146913image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.729095image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.424521image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.288620image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.286072image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:45.985998image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:47.957211image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:50.242076image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:53.711686image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:57.212542image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:59.991211image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:01.999481image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.128073image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.277274image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.631366image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:12.367836image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.828490image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.512624image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.382152image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.392142image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.103568image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.063625image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:50.365143image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:53.837244image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:57.717319image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.183838image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.413093image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.251999image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.501129image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.750961image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:12.560913image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:37.929749image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.637991image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.479887image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.525993image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.230698image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.189826image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:50.483040image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:53.972140image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:57.901927image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.347014image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.509284image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.417579image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile

2024-12-29T11:09:52.315075image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Raw Dataset Profile

2024-12-29T11:09:06.660896image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.866607image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile

2024-12-29T11:09:52.571091image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Raw Dataset Profile

2024-12-29T11:09:12.788741image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.047979image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.769431image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.791151image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:43.672277image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.370614image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.356635image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:50.856906image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:54.113100image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.075252image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.526935image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.634106image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.604085image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.814267image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:08.999413image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:12.947808image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.152009image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.880990image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:41.926968image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:44.003840image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.491811image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.520804image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:51.071003image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:54.976693image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.218829image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.685853image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.743071image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.761809image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:06.940974image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:09.145623image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:13.110569image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:38.267099image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:39.999113image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:42.075285image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:44.242619image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:46.633222image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:48.665973image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:51.294019image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:55.172544image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:08:58.360709image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:00.811583image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:02.864740image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:04.923008image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:07.234800image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile

2024-12-29T11:09:09.303130image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile

2024-12-29T11:09:52.696887image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile


Interaction plot not present for dataset

Raw Dataset Profile


Interaction plot not present for dataset

Preprocessed Dataset Profile

2024-12-29T11:09:52.442427image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Correlations

Raw Dataset Profile

2024-12-29T11:10:37.731060image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Preprocessed Dataset Profile

2024-12-29T11:10:37.925155image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/

Raw Dataset Profile

company_iddire_envio_iddire_recogida_idestadoestadofridid_estadoid_piezaid_tipopeso3tipouser_iduser_id_piezavolumen3web_id
company_id1.0000.4200.5330.0020.0430.1760.0020.1750.0510.1060.0510.6060.6050.6490.349
dire_envio_id0.4201.0000.903-0.043-0.0280.395-0.0430.393-0.0210.107-0.0210.4710.4710.3680.315
dire_recogida_id0.5330.9031.000-0.0720.0400.381-0.0720.381-0.0760.083-0.0760.5260.526NaN0.462
estado0.002-0.043-0.0721.000-0.396-0.0151.000-0.0140.138-0.0350.138-0.003-0.007NaN-0.171
estadofr0.043-0.0280.040-0.3961.000-0.013-0.396-0.0130.5040.4270.504-0.0010.005NaN0.103
id0.1760.3950.381-0.015-0.0131.000-0.0151.000-0.0520.078-0.0510.2990.298-0.0530.185
id_estado0.002-0.043-0.0721.000-0.396-0.0151.000-0.0140.138-0.0350.138-0.003-0.007NaN-0.171
id_pieza0.1750.3930.381-0.014-0.0131.000-0.0141.000-0.0500.078-0.0500.2980.298-0.0510.186
id_tipo0.051-0.021-0.0760.1380.504-0.0520.138-0.0501.0000.4021.000-0.010-0.009NaN-0.226
peso30.1060.1070.083-0.0350.4270.078-0.0350.0780.4021.0000.4020.1050.105NaN0.183
tipo0.051-0.021-0.0760.1380.504-0.0510.138-0.0501.0000.4021.000-0.010-0.009NaN-0.226
user_id0.6060.4710.526-0.003-0.0010.299-0.0030.298-0.0100.105-0.0101.0001.000-0.1080.268
user_id_pieza0.6050.4710.526-0.0070.0050.298-0.0070.298-0.0090.105-0.0091.0001.000-0.1080.268
volumen30.6490.368NaNNaNNaN-0.053NaN-0.051NaNNaNNaN-0.108-0.1081.000NaN
web_id0.3490.3150.462-0.1710.1030.185-0.1710.186-0.2260.183-0.2260.2680.268NaN1.000

Preprocessed Dataset Profile

Fuzzy_Scoreid_pieza
Fuzzy_Score1.0000.057
id_pieza0.0571.000

Missing values

Raw Dataset Profile

2024-12-29T11:09:13.495859image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
A simple visualization of nullity by column.

Preprocessed Dataset Profile

2024-12-29T11:09:52.885907image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
A simple visualization of nullity by column.

Raw Dataset Profile

2024-12-29T11:09:14.186552image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Preprocessed Dataset Profile

2024-12-29T11:09:53.205468image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Raw Dataset Profile

2024-12-29T11:09:16.286052image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Preprocessed Dataset Profile

2024-12-29T11:09:53.434831image/svg+xmlMatplotlib v3.9.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Raw Dataset Profile

idweb_idcodigocreation_datemodification_datecompany_iduser_idref_clienteportes_airzonedevaluacionpedido_sageabono_sagepedido_a3abono_a3tipoestadopersonaazdire_envio_iddire_recogida_idpeso3volumen3estadofrc_mailc_telc_obsaccepted_clientdesc_problemacodigo_incidenciaid_piezauser_id_piezacod_articulodescripcionnum_seriefactura_albaranproblemais_replacementcreation_date_piezamodification_date_piezaid_estadorefcolorvalortitulo_estitulo_entitulo_frtitulo_ittitulo_ptid_tipotitulo_es_tipotitulo_en_tipotitulo_fr_tipotitulo_it_tipotitulo_pt_tipo
0195521MGHQM2LT552020-01-02 09:04:372020-01-20 10:06:04208314PAL19064600NoneNone82000027 / 72000159None2.05.0None<NA><NA>NaNNaN4NoneNoneNoneacceptedSolicitamos cambio de termostatos cables a termostatos inalámbricos.MGHQM2LT5529463314AZCE6BLUEFACECBTERMOSTATO BLUEFACE CABLE BLANCONO DISPONI1/11912209NECESITAMOS CAMBIO A TERMOSTATO THINK RADIO BLANCO.02020-01-02 09:03:182020-01-02 09:03:185GARANTIA-ESF7A54A80R.ValidadaAccepted pickupRetour acceptéVerifica resoNone2devolucionreturnretourritornoNone
1195521MGHQM2LT552020-01-02 09:04:372020-01-20 10:06:04208314PAL19064600NoneNone82000027 / 72000159None2.05.0None<NA><NA>NaNNaN4NoneNoneNoneacceptedSolicitamos cambio de termostatos cables a termostatos inalámbricos.MGHQM2LT5529464314AZCE6LITECBTERMOSTATO LITE BLANCO CABLENO DISPONI1/11912209NECESITAMOS CAMBIO A TERMOSTATO LITE RADIO BLANCO, 3 UDS.02020-01-02 09:04:222020-01-02 09:04:225GARANTIA-ESF7A54A80R.ValidadaAccepted pickupRetour acceptéVerifica resoNone2devolucionreturnretourritornoNone
2195531LMPOM2TR8B2020-01-02 09:34:162020-02-07 12:40:373173CAMBIO TERMOSTATO LITE00NoneNone82000028/72000160620005372.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedNECESITAMOS QUE NOS ENVIEN 1 TERMOSTATO AZRA6LITERB, NO HAY POSIBLILIDAD DE PONERLO CABLELMPOM2TR8B2946573AZRA6LITECBTERMOSTATO LITE CABLE BLANCOF00K2QH1/11916095NECCESITAMOS QUE NOS ENVIEN 1 TERMOSTATO RADIO\r\nAZRA6LITERB02020-01-02 09:34:122020-01-02 09:34:126GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
3195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294664168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00HJNZNoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:48:422020-01-02 10:48:426GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
4195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294674168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSS7NoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:49:122020-01-02 10:49:126GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
5195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294684168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSSCNoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:49:402020-01-02 10:49:406GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
6195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294694168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSSBNoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:50:032020-01-02 10:50:036GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
7195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294704168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSQ3NoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:50:252020-01-02 10:50:256GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
8195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294714168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSS8NoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:50:532020-01-02 10:50:536GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
9195541LMNWLG1U1A2020-01-02 10:52:382020-01-28 07:03:28674168PASARELAS SAMSUNG00NoneNone82000030620003982.06.0None<NA><NA>NaNNaN4NoneNoneNonenotifiedSE REALIZA MYZONE TRAS CONSULTAR A CARLOS FERNANDEZ.\r\nAPARECEN EN EL INVENTARIO ESTAS PASARELAS QUE SE HAN PEDIDO POR ERROR.LMNWLG1U1A294724168AZX6QADAPTSAMPASARELA SAMSUNG NO NASA00LSQ0NoneSOLICITUD DEVOLUCIÓN O REPROCESO A LA SAM202020-01-02 10:51:152020-01-02 10:51:156GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone

Preprocessed Dataset Profile

codigoid_piezacod_articulodesc_problema_translateddescripcion_translatedproblema_translatedCODART_A3Fuzzy_ScoreCODARTDESCARTCAR1CAR2CAR3CAR4text_to_analyseprocessed_text_to_analyse
0MMZPL2LO5029479AZXWSCLOUDWIFIDespués del diagnóstico de HOTLINENoneNo más comunicación, asociación WIFI imposible.AZXWSCLOUDWIFI100.0AZXWSCLOUDWIFIWebserver Airzone Cloud Wi-Fi (2013)126093NoneDespués del diagnóstico de HOTLINE No más comunicación, asociación WIFI imposible.diagnostico hotline comunicacion asociacion wifi imposible
1MMZPL2LO5029480AZX6QADAPTHITDespués del diagnóstico de HOTLINEPasarela de comunicaciones HITACHI RPIproblema de comunicacionAZX6QADAPTHIT100.0AZX6QADAPTHITPasarela comunicaciones Airzone-Hitachi RPI126049NoneDespués del diagnóstico de HOTLINE Pasarela de comunicaciones HITACHI RPI problema de comunicaciondiagnostico hotline pasarela comunicaciones hitachi rpi problema comunicacion
2MMZPL2LO5029481AZX6QADAPTHITDespués del diagnóstico de HOTLINEPuerta de enlace de comunicaciónproblema de comunicacionAZX6QADAPTHIT100.0AZX6QADAPTHITPasarela comunicaciones Airzone-Hitachi RPI126049NoneDespués del diagnóstico de HOTLINE Puerta de enlace de comunicación problema de comunicaciondiagnostico hotline puerta enlace comunicacion problema comunicacion
3L2VQL2LVF329482AZX6CCPCAMBIO CPP EN GARANTIA POR PROBLEMAS COMUNICACIONCENTRAL DE PRODUCCIONfallo en comunicacion central de produccionAZX6CCP100.0AZX6CCPCentral de control de producción Airzone126092NoneCAMBIO CPP EN GARANTIA POR PROBLEMAS COMUNICACION CENTRAL DE PRODUCCION fallo en comunicacion central de produccioncambio cpp garantia problemas comunicacion central produccion fallo comunicacion central produccion
4LGRPLMLUAE29487AZCE6EXP8ZTARJETA POTENTE PARA 8 ZONAS0000RASAZCE6EXP8Z100.0AZCE6EXP8ZMódulo de expansión Airzone 2 zonas (7 y 8)125090NoneTARJETA POTENTE PARA 8 ZONAS 0000 RAStarjeta potente 8 zonas 0000 ras
5MMDTLWPUAF29490AZCE6BLUEFACECBSE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONEMANDOMANDO QUE NO FUNCIONAAZCE6BLUEFACECB100.0AZCE6BLUEFACECBTermostato cable a color Airzone Blueface blanco 8Z (CE6)1250911SE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONE MANDO MANDO QUE NO FUNCIONAsuministraron termostatos solicitamos cambiar garantia funcionan consulta dpto tecnico airzone mando mando funciona
6MMDTLWPUAF29491AZCE6BLUEFACECBSE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONEMANDOMANDO QUE NO FUNCIONAAZCE6BLUEFACECB100.0AZCE6BLUEFACECBTermostato cable a color Airzone Blueface blanco 8Z (CE6)1250911SE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONE MANDO MANDO QUE NO FUNCIONAsuministraron termostatos solicitamos cambiar garantia funcionan consulta dpto tecnico airzone mando mando funciona
7MMDTLWPUAF29492AZCE6BLUEFACECBSE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONEMANDOMANDO QUE NO FUNCIONAAZCE6BLUEFACECB100.0AZCE6BLUEFACECBTermostato cable a color Airzone Blueface blanco 8Z (CE6)1250911SE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONE MANDO MANDO QUE NO FUNCIONAsuministraron termostatos solicitamos cambiar garantia funcionan consulta dpto tecnico airzone mando mando funciona
8MMDTLWPUAF29493AZCE6BLUEFACECBSE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONEMANDOMANDO QUE NO FUNCIONAAZCE6BLUEFACECB100.0AZCE6BLUEFACECBTermostato cable a color Airzone Blueface blanco 8Z (CE6)1250911SE SUMINISTRARON TERMOSTATOS QUE AHORA SOLICITAMOS CAMBIAR EN GARANTÍA, DADO QUE NO FUNCIONAN TRAS REALIZAR LA CONSULTA CON EL DPTO TÉCNICO DE AIRZONE MANDO MANDO QUE NO FUNCIONAsuministraron termostatos solicitamos cambiar garantia funcionan consulta dpto tecnico airzone mando mando funciona
9M2NXM2LRDA29522AZCE6BLUEFACECBBlueface No funcional visto con Sylvain Giraud por teléfonoBlueface PRO 6 BlancBlueFace no funciona después del cambio por una nueva instalación.AZCE6BLUEFACECB100.0AZCE6BLUEFACECBTermostato cable a color Airzone Blueface blanco 8Z (CE6)1250911Blueface No funcional visto con Sylvain Giraud por teléfono Blueface PRO 6 Blanc BlueFace no funciona después del cambio por una nueva instalación.blueface funcional visto sylvain giraud telefono blueface pro 6 blanc blueface funciona cambio instalacion

Raw Dataset Profile

idweb_idcodigocreation_datemodification_datecompany_iduser_idref_clienteportes_airzonedevaluacionpedido_sageabono_sagepedido_a3abono_a3tipoestadopersonaazdire_envio_iddire_recogida_idpeso3volumen3estadofrc_mailc_telc_obsaccepted_clientdesc_problemacodigo_incidenciaid_piezauser_id_piezacod_articulodescripcionnum_seriefactura_albaranproblemais_replacementcreation_date_piezamodification_date_piezaid_estadorefcolorvalortitulo_estitulo_entitulo_frtitulo_ittitulo_ptid_tipotitulo_es_tipotitulo_en_tipotitulo_fr_tipotitulo_it_tipotitulo_pt_tipo
70413647461MMDRAWZM9F2024-09-30 15:54:422024-10-07 07:13:28677667SDC24000985SDV2400068910NoneNone72401975724044651.06.0240908157709070901.0NaN1NoneNoneNoneNoneNoneMMDRAWZM9F1018457667AZDI6BLUEZEROCBTERMOSTATO AIRZONE BLUEFACE ZERO BLANCO 32 Z AZDI6NJ0153**02024-09-30 15:54:402024-09-30 15:54:406GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone1garantiaguaranteegarantiegaranziaNone
70414647471L2NUAWXOE72024-09-30 16:00:352024-10-01 06:14:10595764OFERTA 01/0810NoneNoneNoneNone2.076.0None<NA><NA>NaNNaN0NoneNoneNoneNoneANULACIÓN. SE MODIFICA LA INSTALACIÓN Y NECESITAMOS COLOCAR OTRA DE MAYOR TAMAÑOL2NUAWXOE7101846764RDHVD20010BKRTREJILLA 2 DEFLEX H/V + REG 200X100 BLANCO000E10VY1/22417026DEVOLUCIÓN. SE MODIFICA LA INSTALACIÓN Y NECESITAMOS COLOCAR UNA DE MAYOR TAMAÑO.02024-09-30 15:59:512024-09-30 15:59:5176GARANTIA-ESCC0000100AnuladaAnuladaENAnnuléeAnnullataNone2devolucionreturnretourritornoNone
70415647483MWHPBGHQD62024-09-30 16:17:322024-10-11 07:03:33194524346240053410NoneNoneAS08248454724010802.06.0None<NA>89430.9NaN43NoneNoneNoneNonerendiamo scheda centrale non funzionante cambiata alla cliente AS0824854MWHPBGHQD61018472434AZPV8CB1IAQSCHEDA CENTRALE AIRZONE EZ88445409124AS08248454RENDIAMO RICAMBIO NON FUNZIONANTE02024-09-30 16:17:302024-09-30 16:17:306GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70416647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710184810229AZCE6THINKRBNoneF02236J72401291CAMBIADO02024-09-30 16:41:542024-09-30 16:41:546GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70417647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710184910229AZCE6THINKRBNoneF02236B72401291CAMBIADO02024-09-30 16:42:332024-09-30 16:42:336GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70418647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710185010229AZCE6THINKRBNoneF02236A72401291CAMBIADO02024-09-30 16:43:062024-09-30 16:43:066GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70419647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710185110229AZCE6THINKRBNoneF02236I72401291CAMBIADO02024-09-30 16:43:372024-09-30 16:43:376GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70420647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710185210229AZCE6THINKRBNoneF02236F72401291CAMBIADO02024-09-30 16:44:092024-09-30 16:44:096GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70421647491MMLVBGDJ972024-09-30 16:44:482024-10-03 10:59:16763010229PM477678310NoneNoneRMA_PM4776783724044362.06.0None<NA>215422.0NaN4NoneNoneNoneNoneTERMOSTATOS SUSTITUIDOSMMLVBGDJ9710185310229AZCE6THINKRBNoneF02236D72401291CAMBIADO02024-09-30 16:44:422024-09-30 16:44:426GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone2devolucionreturnretourritornoNone
70422647501NWNYZMPP9D2024-09-30 18:10:262024-10-22 11:39:0621172629RAirzone01202410NoneNone72401977724047431.06.024090790323447234470.5NaN1NoneNoneNoneNoneEl sistema ha perdido la conexión con la aplicación. Se ha reseteado el sistema por completo varias veces, y todo funciona correctamente, salvo la conexión con el Webserver.NWNYZMPP9D1018542629--AZX6WSC5GER Webserver Airzone Cloud Wifi dual 2,4---Su Factura Nº 1/12305297Sustitución del Webserver por no comunicar, problema de comunicación.02024-09-30 18:09:252024-09-30 18:09:256GARANTIA-ES18A689100CerradaClosedFerméeChiusaNone1garantiaguaranteegarantiegaranziaNone

Preprocessed Dataset Profile

codigoid_piezacod_articulodesc_problema_translateddescripcion_translatedproblema_translatedCODART_A3Fuzzy_ScoreCODARTDESCARTCAR1CAR2CAR3CAR4text_to_analyseprocessed_text_to_analyse
19349MMPVAMVPAD92802AZCE8CB1DINen la puesta en marcha 1 central y un modulo no funciona, el técnico de airzone, nos comunico que se pidiera en garantía estos dos aparatos, dicho técnico le dio al cliente una numeración que es el 240404312.\r\n\r\nNecesitamos con urgencia el recambio del material, por que el cliente tiene que cerrar la obra.CENTRAL AIRZONE PARA FLEXA 4.0 EN CARRIL DINen la puesta en marcha 1 central y un modulo no funcionaAZCE8CB1DIN100.0AZCE8CB1DINCentral Airzone para Flexa 4.0 en carril DIN para control radiante frío/calor (8z)127090108en la puesta en marcha 1 central y un modulo no funciona, el técnico de airzone, nos comunico que se pidiera en garantía estos dos aparatos, dicho técnico le dio al cliente una numeración que es el 240404312.\r\n\r\nNecesitamos con urgencia el recambio del material, por que el cliente tiene que cerrar la obra. CENTRAL AIRZONE PARA FLEXA 4.0 EN CARRIL DIN en la puesta en marcha 1 central y un modulo no funcionapuesta marcha 1 central modulo funciona tecnico airzone comunico pidiera garantia aparatos tecnico cliente numeracion 240404312 necesitamos urgencia recambio material cliente cerrar obra central airzone flexa 4.0 carril din puesta marcha 1 central modulo funciona
19350MMPVAMVPAD92803AZCE8CM1VALCen la puesta en marcha 1 central y un modulo no funciona, el técnico de airzone, nos comunico que se pidiera en garantía estos dos aparatos, dicho técnico le dio al cliente una numeración que es el 240404312.\r\n\r\nNecesitamos con urgencia el recambio del material, por que el cliente tiene que cerrar la obra.MÓDULO DE CONTROL AIRZONE FLEXA 4.0 DE VÁLNO FUNCIONA LA PUESTA EN MARCHAAZCE8CM1VALC100.0AZCE8CM1VALCMódulo de control Airzone Flexa 4.0 cabezales termostáticos cableados 110/230V VALC127094Noneen la puesta en marcha 1 central y un modulo no funciona, el técnico de airzone, nos comunico que se pidiera en garantía estos dos aparatos, dicho técnico le dio al cliente una numeración que es el 240404312.\r\n\r\nNecesitamos con urgencia el recambio del material, por que el cliente tiene que cerrar la obra. MÓDULO DE CONTROL AIRZONE FLEXA 4.0 DE VÁL NO FUNCIONA LA PUESTA EN MARCHApuesta marcha 1 central modulo funciona tecnico airzone comunico pidiera garantia aparatos tecnico cliente numeracion 240404312 necesitamos urgencia recambio material cliente cerrar obra modulo control airzone flexa 4.0 val funciona puesta marcha
19351L2NTBGLNDE92918AZDI6MZZONCEL MODULO DE ZONA CABLE MOTOR NO TIENE COMUNICACION CON LA CENTRALMódulo zona cable motor Airzone 32ZENVIAR UN MODULO DE ZONA NUEVOAZDI6MZZONC100.0AZDI6MZZONCModulo zona motor cable Airzone 32Z125195NoneEL MODULO DE ZONA CABLE MOTOR NO TIENE COMUNICACION CON LA CENTRAL Módulo zona cable motor Airzone 32Z ENVIAR UN MODULO DE ZONA NUEVOmodulo zona cable motor comunicacion central modulo zona cable motor airzone 32z enviar modulo zona
19352N2NXAWVJA892948AZCE6FLEXA3La placa central viene averiada. Según hemos visto por fuera parece como de haber sido usada ya que viene pintada, (aunque la caja venia precintada)\r\nTras hablar con el servicio tecnico de airzone nos dieron este codigo 240403168 para tramitar la garantia.CENT.AIRZONE FLEXA 3.0 6Z AZCE6FLEXA3necesitamos tramitar la garantia de la central Airzone que os compramos. La placa central viene averiada. Según hemos visto por fuera parece como de haber sido usada ya que viene pintada, (aunque la caja venia precintada)\r\nTras hablar con el serviciAZCE6FLEXA3100.0AZCE6FLEXA3Central de sistema Airzone Flexa 3.0 6Z125090NoneLa placa central viene averiada. Según hemos visto por fuera parece como de haber sido usada ya que viene pintada, (aunque la caja venia precintada)\r\nTras hablar con el servicio tecnico de airzone nos dieron este codigo 240403168 para tramitar la garantia. CENT.AIRZONE FLEXA 3.0 6Z AZCE6FLEXA3 necesitamos tramitar la garantia de la central Airzone que os compramos. La placa central viene averiada. Según hemos visto por fuera parece como de haber sido usada ya que viene pintada, (aunque la caja venia precintada)\r\nTras hablar con el serviciplaca central viene averiada visto usada viene pintada caja venia precintada hablar servicio tecnico airzone codigo 240403168 tramitar garantia cent.airzone flexa 3.0 6z azce6flexa3 necesitamos tramitar garantia central airzone compramos placa central viene averiada visto usada viene pintada caja venia precintada hablar servici
19353MGLWAWVH2692962AZCE6CB1MOTSEGÚN CONVERSACIÓN CON CLIENTEFLEXIÓN CENTRAL 3.0SEGÚN CONVERSACIÓN CON CLIENTEAZCE8CB1MOT91.0AZCE8CB1MOTCentral de sistema Airzone Flexa 4.0 (CE8)127090NoneSEGÚN CONVERSACIÓN CON CLIENTE FLEXIÓN CENTRAL 3.0 SEGÚN CONVERSACIÓN CON CLIENTEconversacion cliente flexion central 3.0 conversacion cliente
19354MWLVZMNQFD92992AZDI6OUTPUT8NoneMODULO CTROL.ELEM.RADIANTE 32 Z.AIRZONE (AZDI6OUTP*AZDI6OUTPUT8100.0AZDI6OUTPUT8Modulo control elementos radiantes Airzone 32Z125194NoneMODULO CTROL.ELEM.RADIANTE 32 Z.AIRZONE (AZDI6OUTP *modulo ctrol.elem.radiante 32 z.airzone azdi6outp
19355MWLVZMNQFD92993AZDI6MZZONCNoneMODULO ZONIFICACION 32 ZONAS CABLE (AZDI6MZZONC)*AZDI6MZZONC100.0AZDI6MZZONCModulo zona motor cable Airzone 32Z125195NoneMODULO ZONIFICACION 32 ZONAS CABLE (AZDI6MZZONC) *modulo zonificacion 32 zonas cable azdi6mzzonc
19356MWRUZ2LL6692996AZX6WEBSCLOUDCWEBSERVER NO FUNCIONASERVIDOR WEBWEBSERVER NO FUNCIONA. REVISADO POR SAT TELEFONICO.AZX6WEBSCLOUDC100.0AZX6WEBSCLOUDCWebserver Airzone cloud cable ethernet126093NoneWEBSERVER NO FUNCIONA SERVIDOR WEB WEBSERVER NO FUNCIONA. REVISADO POR SAT TELEFONICO.webserver funciona servidor web webserver funciona revisado sat telefonico
19357MGHUZGPLFB93097MINT / AZPV0MOTRDEVOLUCION MATERIAL EN GARANTIAMOTOR INTELIGENTE DOBLEREPOSICION EN GARANTIAMINT100.0MINTMotor de rejilla inteligente doble - sustituido por AZPV0MOTRMD126480NoneDEVOLUCION MATERIAL EN GARANTIA MOTOR INTELIGENTE DOBLE REPOSICION EN GARANTIAdevolucion material garantia motor inteligente doble reposicion garantia
19358MGHUZGPLFB93099MINT / AZPV0MOTRDEVOLUCION MATERIAL EN GARANTIAMOTOR INTELIGENTE DOBLEREPOSICION EN GARANTIAMINT100.0MINTMotor de rejilla inteligente doble - sustituido por AZPV0MOTRMD126480NoneDEVOLUCION MATERIAL EN GARANTIA MOTOR INTELIGENTE DOBLE REPOSICION EN GARANTIAdevolucion material garantia motor inteligente doble reposicion garantia

Duplicate rows

Raw Dataset Profile

idweb_idcodigocreation_datemodification_datecompany_iduser_idref_clienteportes_airzonedevaluacionpedido_a3abono_a3tipoestadopersonaazdire_envio_iddire_recogida_idpeso3volumen3estadofrc_mailc_telc_obsaccepted_clientdesc_problemacodigo_incidenciaid_piezauser_id_piezacod_articulodescripcionnum_seriefactura_albaranproblemais_replacementcreation_date_piezamodification_date_piezaid_estadorefcolorvalortitulo_estitulo_entitulo_frtitulo_itid_tipotitulo_es_tipotitulo_en_tipotitulo_fr_tipotitulo_it_tipo# duplicates
Dataset does not contain duplicate rows.

Preprocessed Dataset Profile

codigoid_piezacod_articulodesc_problema_translateddescripcion_translatedproblema_translatedCODART_A3Fuzzy_ScoreCODARTDESCARTCAR1CAR2CAR3CAR4text_to_analyseprocessed_text_to_analyse# duplicates
Dataset does not contain duplicate rows.